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- affiliation: Boston University, MA, USA
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2020 – today
- 2024
[j55]Ping Hu
, Simon Niklaus, Lu Zhang, Stan Sclaroff, Kate Saenko:
Video Frame Interpolation With Many-to-Many Splatting and Spatial Selective Refinement. IEEE Trans. Pattern Anal. Mach. Intell. 46(2): 823-836 (2024)- [j54]Ping Hu, Ximeng Sun, Stan Sclaroff, Kate Saenko:
DualCoOp++: Fast and Effective Adaptation to Multi-Label Recognition With Limited Annotations. IEEE Trans. Pattern Anal. Mach. Intell. 46(5): 3450-3462 (2024) - 2023
- [j53]Nataniel Ruiz, Hao Yu, Danielle Allessio, Mona Jalal, Ajjen Joshi, Tom Murray, John J. Magee, Kevin Delgado, Vitaly Ablavsky, Stan Sclaroff, Ivon Arroyo, Beverly P. Woolf, Sarah Adel Bargal, Margrit Betke:
ATL-BP: A Student Engagement Dataset and Model for Affect Transfer Learning for Behavior Prediction. IEEE Trans. Biom. Behav. Identity Sci. 5(3): 411-424 (2023) - [c160]Nataniel Ruiz, Sarah Adel Bargal, Cihang Xie, Stan Sclaroff:
Practical Disruption of Image Translation Deepfake Networks. AAAI 2023: 14478-14486 - [c159]Milind Naphade, Shuo Wang, David C. Anastasiu, Zheng Tang, Ming-Ching Chang, Yue Yao, Liang Zheng, Mohammed Shaiqur Rahman, Meenakshi S. Arya, Anuj Sharma, Qi Feng, Vitaly Ablavsky, Stan Sclaroff, Pranamesh Chakraborty, Sanjita Prajapati, Alice Li, Shangru Li, Krishna Kunadharaju, Shenxin Jiang, Rama Chellappa:
The 7th AI City Challenge. CVPR Workshops 2023: 5538-5548 - [i56]Milind Naphade, Shuo Wang, David C. Anastasiu, Zheng Tang, Ming-Ching Chang, Yue Yao, Liang Zheng, Mohammed Shaiqur Rahman, Meenakshi S. Arya, Anuj Sharma, Qi Feng, Vitaly Ablavsky, Stan Sclaroff, Pranamesh Chakraborty, Sanjita Prajapati, Alice Li, Shangru Li, Krishna Kunadharaju, Shenxin Jiang, Rama Chellappa:
The 7th AI City Challenge. CoRR abs/2304.07500 (2023) - [i55]Ariel N. Lee, Sarah Adel Bargal, Janavi Kasera, Stan Sclaroff, Kate Saenko, Nataniel Ruiz:
Hardwiring ViT Patch Selectivity into CNNs using Patch Mixing. CoRR abs/2306.17848 (2023) - [i54]Ping Hu, Ximeng Sun, Stan Sclaroff, Kate Saenko:
DualCoOp++: Fast and Effective Adaptation to Multi-Label Recognition with Limited Annotations. CoRR abs/2308.01890 (2023) - [i53]Ping Hu, Simon Niklaus, Lu Zhang, Stan Sclaroff, Kate Saenko:
Video Frame Interpolation with Many-to-many Splatting and Spatial Selective Refinement. CoRR abs/2310.18946 (2023) - 2022
- [j52]Shoumik Sovan Majumdar, Shubhangi Jain, Isidora Chara Tourni, Arsenii Mustafin, Diala Lteif, Stan Sclaroff, Kate Saenko, Sarah Adel Bargal:
Ani-GIFs: A benchmark dataset for domain generalization of action recognition from GIFs. Frontiers Comput. Sci. 4 (2022) - [j51]Bryan A. Plummer, Kevin J. Shih, Yichen Li, Ke Xu, Svetlana Lazebnik, Stan Sclaroff, Kate Saenko:
Revisiting Image-Language Networks for Open-Ended Phrase Detection. IEEE Trans. Pattern Anal. Mach. Intell. 44(4): 2155-2167 (2022) - [j50]Ping Hu, Stan Sclaroff, Kate Saenko:
Leveraging Geometric Structure for Label-Efficient Semi-Supervised Scene Segmentation. IEEE Trans. Image Process. 31: 6320-6330 (2022) - [c158]Milind Naphade, Shuo Wang, David C. Anastasiu, Zheng Tang, Ming-Ching Chang, Yue Yao, Liang Zheng, Mohammed Shaiqur Rahman, Archana Venkatachalapathy, Anuj Sharma, Qi Feng, Vitaly Ablavsky, Stan Sclaroff, Pranamesh Chakraborty, Alice Li, Shangru Li, Rama Chellappa:
The 6th AI City Challenge. CVPR Workshops 2022: 3346-3355 - [c157]Ping Hu, Simon Niklaus, Stan Sclaroff, Kate Saenko:
Many-to-many Splatting for Efficient Video Frame Interpolation. CVPR 2022: 3543-3552 - [c156]Nataniel Ruiz, Adam Kortylewski, Weichao Qiu, Cihang Xie, Sarah Adel Bargal, Alan L. Yuille, Stan Sclaroff:
Simulated Adversarial Testing of Face Recognition Models. CVPR 2022: 4135-4145 - [c155]Donghyun Kim, Kaihong Wang, Kate Saenko, Margrit Betke, Stan Sclaroff:
A Unified Framework for Domain Adaptive Pose Estimation. ECCV (33) 2022: 603-620 - [c154]Donghyun Kim, Kaihong Wang, Stan Sclaroff, Kate Saenko:
A Broad Study of Pre-training for Domain Generalization and Adaptation. ECCV (33) 2022: 621-638 - [c153]Marc Oliu, Sarah Adel Bargal, Stan Sclaroff, Xavier Baró, Sergio Escalera:
Multi-varied Cumulative Alignment for Domain Adaptation. ICIAP (2) 2022: 324-334 - [c152]Nataniel Ruiz, Sarah A. Bargal, Cihang Xie, Kate Saenko, Stan Sclaroff:
Finding Differences Between Transformers and ConvNets Using Counterfactual Simulation Testing. NeurIPS 2022 - [e13]Stan Sclaroff, Cosimo Distante, Marco Leo, Giovanni Maria Farinella, Federico Tombari:
Image Analysis and Processing - ICIAP 2022 - 21st International Conference, Lecce, Italy, May 23-27, 2022, Proceedings, Part I. Lecture Notes in Computer Science 13231, Springer 2022, ISBN 978-3-031-06426-5 [contents] - [e12]Stan Sclaroff, Cosimo Distante, Marco Leo, Giovanni Maria Farinella, Federico Tombari:
Image Analysis and Processing - ICIAP 2022 - 21st International Conference, Lecce, Italy, May 23-27, 2022, Proceedings, Part II. Lecture Notes in Computer Science 13232, Springer 2022, ISBN 978-3-031-06429-6 [contents] - [e11]Stan Sclaroff, Cosimo Distante, Marco Leo, Giovanni Maria Farinella, Federico Tombari:
Image Analysis and Processing - ICIAP 2022 - 21st International Conference, Lecce, Italy, May 23-27, 2022, Proceedings, Part III. Lecture Notes in Computer Science 13233, Springer 2022, ISBN 978-3-031-06432-6 [contents] - [e10]Pier Luigi Mazzeo, Emanuele Frontoni, Stan Sclaroff, Cosimo Distante:
Image Analysis and Processing. ICIAP 2022 Workshops - ICIAP International Workshops, Lecce, Italy, May 23-27, 2022, Revised Selected Papers, Part I. Lecture Notes in Computer Science 13373, Springer 2022, ISBN 978-3-031-13320-6 [contents] - [e9]Pier Luigi Mazzeo, Emanuele Frontoni, Stan Sclaroff, Cosimo Distante:
Image Analysis and Processing. ICIAP 2022 Workshops - ICIAP International Workshops, Lecce, Italy, May 23-27, 2022, Revised Selected Papers, Part II. Lecture Notes in Computer Science 13374, Springer 2022, ISBN 978-3-031-13323-7 [contents] - [i52]Donghyun Kim, Kaihong Wang, Stan Sclaroff, Kate Saenko:
A Broad Study of Pre-training for Domain Generalization and Adaptation. CoRR abs/2203.11819 (2022) - [i51]Donghyun Kim, Kaihong Wang, Kate Saenko, Margrit Betke, Stan Sclaroff:
A Unified Framework for Domain Adaptive Pose Estimation. CoRR abs/2204.00172 (2022) - [i50]Ping Hu, Simon Niklaus, Stan Sclaroff, Kate Saenko:
Many-to-many Splatting for Efficient Video Frame Interpolation. CoRR abs/2204.03513 (2022) - [i49]Milind Naphade, Shuo Wang, David C. Anastasiu, Zheng Tang, Ming-Ching Chang, Yue Yao, Liang Zheng, Mohammed Shaiqur Rahman, Archana Venkatachalapathy, Anuj Sharma, Qi Feng, Vitaly Ablavsky, Stan Sclaroff, Pranamesh Chakraborty, Alice Li, Shangru Li, Rama Chellappa:
The 6th AI City Challenge. CoRR abs/2204.10380 (2022) - [i48]Quanfu Fan, Donghyun Kim, Chun-Fu Chen, Stan Sclaroff, Kate Saenko, Sarah Adel Bargal:
Temporal Relevance Analysis for Video Action Models. CoRR abs/2204.11929 (2022) - [i47]Nataniel Ruiz, Sarah Adel Bargal, Cihang Xie, Kate Saenko, Stan Sclaroff:
Finding Differences Between Transformers and ConvNets Using Counterfactual Simulation Testing. CoRR abs/2211.16499 (2022) - 2021
- [j49]Andrea Zunino, Sarah Adel Bargal, Pietro Morerio, Jianming Zhang, Stan Sclaroff, Vittorio Murino:
Excitation Dropout: Encouraging Plasticity in Deep Neural Networks. Int. J. Comput. Vis. 129(4): 1139-1152 (2021) - [j48]Sarah Adel Bargal, Andrea Zunino, Vitali Petsiuk, Jianming Zhang, Kate Saenko, Vittorio Murino, Stan Sclaroff:
Guided Zoom: Zooming into Network Evidence to Refine Fine-Grained Model Decisions. IEEE Trans. Pattern Anal. Mach. Intell. 43(11): 4196-4202 (2021) - [j47]Ping Hu, Federico Perazzi, Fabian Caba Heilbron, Oliver Wang, Zhe Lin, Kate Saenko, Stan Sclaroff:
Real-Time Semantic Segmentation With Fast Attention. IEEE Robotics Autom. Lett. 6(1): 263-270 (2021) - [c151]Andrea Zunino, Sarah Adel Bargal, Riccardo Volpi, Mehrnoosh Sameki, Jianming Zhang, Stan Sclaroff, Vittorio Murino, Kate Saenko:
Explainable Deep Classification Models for Domain Generalization. CVPR Workshops 2021: 3233-3242 - [c150]Milind Naphade, Shuo Wang, David C. Anastasiu, Zheng Tang, Ming-Ching Chang, Xiaodong Yang, Yue Yao, Liang Zheng, Pranamesh Chakraborty, Christian E. López, Anuj Sharma, Qi Feng, Vitaly Ablavsky, Stan Sclaroff:
The 5th AI City Challenge. CVPR Workshops 2021: 4263-4273 - [c149]Qi Feng, Vitaly Ablavsky, Qinxun Bai, Stan Sclaroff:
Siamese Natural Language Tracker: Tracking by Natural Language Descriptions With Siamese Trackers. CVPR 2021: 5851-5860 - [c148]Nataniel Ruiz, Hao Yu, Danielle Allessio, Mona Jalal, Ajjen Joshi, Thomas J. Murray, John J. Magee, Jacob Whitehill, Vitaly Ablavsky, Ivon Arroyo, Beverly P. Woolf, Stan Sclaroff, Margrit Betke:
Leveraging Affect Transfer Learning for Behavior Prediction in an Intelligent Tutoring System. FG 2021: 1-8 - [c147]Donghyun Kim, Kuniaki Saito, Tae-Hyun Oh, Bryan A. Plummer, Stan Sclaroff, Kate Saenko:
CDS: Cross-Domain Self-supervised Pre-training. ICCV 2021: 9103-9112 - [c146]Kuniaki Saito, Donghyun Kim, Piotr Teterwak, Stan Sclaroff, Trevor Darrell, Kate Saenko:
Tune it the Right Way: Unsupervised Validation of Domain Adaptation via Soft Neighborhood Density. ICCV 2021: 9164-9173 - [c145]Donghyun Kim, Yi-Hsuan Tsai, Bingbing Zhuang, Xiang Yu, Stan Sclaroff, Kate Saenko, Manmohan Chandraker:
Learning Cross-Modal Contrastive Features for Video Domain Adaptation. ICCV 2021: 13598-13607 - [c144]Donghyun Kim, Kuniaki Saito, Samarth Mishra, Stan Sclaroff, Kate Saenko, Bryan A. Plummer:
Self-supervised Visual Attribute Learning for Fashion Compatibility. ICCVW 2021: 1057-1066 - [c143]Donghyun Kim, Tian Lan, Chuhang Zou, Ning Xu, Bryan A. Plummer, Stan Sclaroff, Jayan Eledath, Gérard G. Medioni:
MILA: Multi-Task Learning from Videos via Efficient Inter-Frame Attention. ICCVW 2021: 2219-2229 - [c142]Nuno Cruz Garcia, Sarah Adel Bargal, Vitaly Ablavsky, Pietro Morerio, Vittorio Murino, Stan Sclaroff:
Distillation Multiple Choice Learning for Multimodal Action Recognition. WACV 2021: 2754-2763 - [e8]Alberto Del Bimbo, Rita Cucchiara, Stan Sclaroff, Giovanni Maria Farinella, Tao Mei, Marco Bertini, Hugo Jair Escalante, Roberto Vezzani:
Pattern Recognition. ICPR International Workshops and Challenges - Virtual Event, January 10-15, 2021, Proceedings, Part I. Lecture Notes in Computer Science 12661, Springer 2021, ISBN 978-3-030-68762-5 [contents] - [e7]Alberto Del Bimbo, Rita Cucchiara, Stan Sclaroff, Giovanni Maria Farinella, Tao Mei, Marco Bertini, Hugo Jair Escalante, Roberto Vezzani:
Pattern Recognition. ICPR International Workshops and Challenges - Virtual Event, January 10-15, 2021, Proceedings, Part II. Lecture Notes in Computer Science 12662, Springer 2021, ISBN 978-3-030-68789-2 [contents] - [e6]Alberto Del Bimbo, Rita Cucchiara, Stan Sclaroff, Giovanni Maria Farinella, Tao Mei, Marco Bertini, Hugo Jair Escalante, Roberto Vezzani:
Pattern Recognition. ICPR International Workshops and Challenges - Virtual Event, January 10-15, 2021, Proceedings, Part III. Lecture Notes in Computer Science 12663, Springer 2021, ISBN 978-3-030-68795-3 [contents] - [e5]Alberto Del Bimbo, Rita Cucchiara, Stan Sclaroff, Giovanni Maria Farinella, Tao Mei, Marco Bertini, Hugo Jair Escalante, Roberto Vezzani:
Pattern Recognition. ICPR International Workshops and Challenges - Virtual Event, January 10-15, 2021, Proceedings, Part IV. Lecture Notes in Computer Science 12664, Springer 2021, ISBN 978-3-030-68798-4 [contents] - [e4]Alberto Del Bimbo, Rita Cucchiara, Stan Sclaroff, Giovanni Maria Farinella, Tao Mei, Marco Bertini, Hugo Jair Escalante, Roberto Vezzani:
Pattern Recognition. ICPR International Workshops and Challenges - Virtual Event, January 10-15, 2021, Proceedings, Part V. Lecture Notes in Computer Science 12665, Springer 2021, ISBN 978-3-030-68820-2 [contents] - [e3]Alberto Del Bimbo, Rita Cucchiara, Stan Sclaroff, Giovanni Maria Farinella, Tao Mei, Marco Bertini, Hugo Jair Escalante, Roberto Vezzani:
Pattern Recognition. ICPR International Workshops and Challenges - Virtual Event, January 10-15, 2021, Proceedings, Part VI. Lecture Notes in Computer Science 12666, Springer 2021, ISBN 978-3-030-68779-3 [contents] - [e2]Alberto Del Bimbo, Rita Cucchiara, Stan Sclaroff, Giovanni Maria Farinella, Tao Mei, Marco Bertini, Hugo Jair Escalante, Roberto Vezzani:
Pattern Recognition. ICPR International Workshops and Challenges - Virtual Event, January 10-15, 2021, Proceedings, Part VII. Lecture Notes in Computer Science 12667, Springer 2021, ISBN 978-3-030-68786-1 [contents] - [e1]Alberto Del Bimbo, Rita Cucchiara, Stan Sclaroff, Giovanni Maria Farinella, Tao Mei, Marco Bertini, Hugo Jair Escalante, Roberto Vezzani:
Pattern Recognition. ICPR International Workshops and Challenges - Virtual Event, January 10-15, 2021, Proceedings, Part VIII. Lecture Notes in Computer Science 12668, Springer 2021, ISBN 978-3-030-68792-2 [contents] - [i46]Qi Feng, Vitaly Ablavsky, Stan Sclaroff:
CityFlow-NL: Tracking and Retrieval of Vehicles at City Scale by Natural Language Descriptions. CoRR abs/2101.04741 (2021) - [i45]Milind Naphade, Shuo Wang, David C. Anastasiu, Zheng Tang, Ming-Ching Chang, Xiaodong Yang, Yue Yao, Liang Zheng, Pranamesh Chakraborty, Anuj Sharma, Qi Feng, Vitaly Ablavsky, Stan Sclaroff:
The 5th AI City Challenge. CoRR abs/2104.12233 (2021) - [i44]Nataniel Ruiz, Adam Kortylewski, Weichao Qiu, Cihang Xie, Sarah Adel Bargal, Alan L. Yuille, Stan Sclaroff:
Simulated Adversarial Testing of Face Recognition Models. CoRR abs/2106.04569 (2021) - [i43]Kuniaki Saito, Donghyun Kim, Piotr Teterwak, Stan Sclaroff, Trevor Darrell, Kate Saenko:
Tune it the Right Way: Unsupervised Validation of Domain Adaptation via Soft Neighborhood Density. CoRR abs/2108.10860 (2021) - [i42]Donghyun Kim, Yi-Hsuan Tsai, Bingbing Zhuang, Xiang Yu, Stan Sclaroff, Kate Saenko, Manmohan Chandraker:
Learning Cross-modal Contrastive Features for Video Domain Adaptation. CoRR abs/2108.11974 (2021) - 2020
- [c141]Donghyun Kim, Kuniaki Saito, Kate Saenko, Stan Sclaroff, Bryan A. Plummer:
MULE: Multimodal Universal Language Embedding. AAAI 2020: 11254-11261 - [c140]Ping Hu, Fabian Caba, Oliver Wang, Zhe Lin, Stan Sclaroff, Federico Perazzi:
Temporally Distributed Networks for Fast Video Semantic Segmentation. CVPR 2020: 8815-8824 - [c139]Nataniel Ruiz, Sarah Adel Bargal, Stan Sclaroff:
Disrupting Deepfakes: Adversarial Attacks Against Conditional Image Translation Networks and Facial Manipulation Systems. ECCV Workshops (4) 2020: 236-251 - [c138]Sarah Adel Bargal, Andrea Zunino, Vitali Petsiuk, Jianming Zhang, Vittorio Murino, Stan Sclaroff, Kate Saenko:
Beyond the Visual Analysis of Deep Model Saliency. xxAI@ICML 2020: 255-269 - [c137]Ping Hu, Stan Sclaroff, Kate Saenko:
Uncertainty-Aware Learning for Zero-Shot Semantic Segmentation. NeurIPS 2020 - [c136]Kuniaki Saito, Donghyun Kim, Stan Sclaroff, Kate Saenko:
Universal Domain Adaptation through Self Supervision. NeurIPS 2020 - [c135]Qi Feng, Vitaly Ablavsky, Qinxun Bai, Guorong Li, Stan Sclaroff:
Real-time Visual Object Tracking with Natural Language Description. WACV 2020: 689-698 - [c134]Donghyun Kim, Sarah Adel Bargal, Jianming Zhang, Stan Sclaroff:
Multi-way Encoding for Robustness. WACV 2020: 1341-1349 - [c133]Ping Hu, Jun Liu, Gang Wang, Vitaly Ablavsky, Kate Saenko, Stan Sclaroff:
DIPNet: Dynamic Identity Propagation Network for Video Object Segmentation. WACV 2020: 1893-1902 - [i41]Nataniel Ruiz, Mona Jalal, Vitaly Ablavsky, Danielle Allessio, John J. Magee, Jacob Whitehill, Ivon Arroyo, Beverly P. Woolf, Stan Sclaroff, Margrit Betke:
Leveraging Affect Transfer Learning for Behavior Prediction in an Intelligent Tutoring System. CoRR abs/2002.05242 (2020) - [i40]Donghyun Kim, Tian Lan, Chuhang Zou, Ning Xu, Bryan A. Plummer, Stan Sclaroff, Jayan Eledath, Gérard G. Medioni:
Multi-Task Learning from Videos via Efficient Inter-Frame Attention. CoRR abs/2002.07362 (2020) - [i39]Kuniaki Saito, Donghyun Kim, Stan Sclaroff, Kate Saenko:
Universal Domain Adaptation through Self Supervision. CoRR abs/2002.07953 (2020) - [i38]Nataniel Ruiz, Sarah Adel Bargal, Stan Sclaroff:
Disrupting Deepfakes: Adversarial Attacks Against Conditional Image Translation Networks and Facial Manipulation Systems. CoRR abs/2003.01279 (2020) - [i37]Andrea Zunino, Sarah Adel Bargal, Riccardo Volpi, Mehrnoosh Sameki, Jianming Zhang, Stan Sclaroff, Vittorio Murino, Kate Saenko:
Explainable Deep Classification Models for Domain Generalization. CoRR abs/2003.06498 (2020) - [i36]Donghyun Kim, Kuniaki Saito, Tae-Hyun Oh, Bryan A. Plummer, Stan Sclaroff, Kate Saenko:
Cross-domain Self-supervised Learning for Domain Adaptation with Few Source Labels. CoRR abs/2003.08264 (2020) - [i35]Huijuan Xu, Lizhi Yang, Stan Sclaroff, Kate Saenko, Trevor Darrell:
Spatio-Temporal Action Detection with Multi-Object Interaction. CoRR abs/2004.00180 (2020) - [i34]Ping Hu, Fabian Caba Heilbron, Oliver Wang, Zhe L. Lin, Stan Sclaroff, Federico Perazzi:
Temporally Distributed Networks for Fast Video Semantic Segmentation. CoRR abs/2004.01800 (2020) - [i33]Nataniel Ruiz, Sarah Adel Bargal, Stan Sclaroff:
Protecting Against Image Translation Deepfakes by Leaking Universal Perturbations from Black-Box Neural Networks. CoRR abs/2006.06493 (2020) - [i32]Ping Hu, Federico Perazzi, Fabian Caba Heilbron, Oliver Wang, Zhe Lin, Kate Saenko, Stan Sclaroff:
Real-time Semantic Segmentation with Fast Attention. CoRR abs/2007.03815 (2020) - [i31]Donghyun Kim, Kuniaki Saito, Kate Saenko, Stan Sclaroff, Bryan A. Plummer:
Self-supervised Visual Attribute Learning for Fashion Compatibility. CoRR abs/2008.00348 (2020)
2010 – 2019
- 2019
- [b1]Jianming Zhang, Filip Malmberg, Stan Sclaroff:
Visual Saliency: From Pixel-Level to Object-Level Analysis. Springer 2019, ISBN 978-3-030-04830-3, pp. 1-114 - [j46]Fatih Çakir, Kun He, Sarah Adel Bargal, Stan Sclaroff:
Hashing with Mutual Information. IEEE Trans. Pattern Anal. Mach. Intell. 41(10): 2424-2437 (2019) - [c132]Huijuan Xu, Kun He, Bryan A. Plummer, Leonid Sigal, Stan Sclaroff, Kate Saenko:
Multilevel Language and Vision Integration for Text-to-Clip Retrieval. AAAI 2019: 9062-9069 - [c131]Sarah Adel Bargal, Andrea Zunino, Vitali Petsiuk, Jianming Zhang, Kate Saenko, Vittorio Murino, Stan Sclaroff:
Guided Zoom: Questioning Network Evidence for Fine-grained Classification. BMVC 2019: 17 - [c130]Sarah Adel Bargal, Andrea Zunino, Vitali Petsiuk, Jianming Zhang, Kate Saenko, Vittorio Murino, Stan Sclaroff:
Are CNN Predictions based on Reasonable Evidence? CVPR Workshops 2019: 67-70 - [c129]Fatih Çakir, Kun He, Xide Xia, Brian Kulis, Stan Sclaroff:
Deep Metric Learning to Rank. CVPR 2019: 1861-1870 - [c128]Ajjen Joshi, Danielle Allessio, John J. Magee, Jacob Whitehill, Ivon Arroyo, Beverly P. Woolf, Stan Sclaroff, Margrit Betke:
Affect-driven Learning Outcomes Prediction in Intelligent Tutoring Systems. FG 2019: 1-5 - [c127]Hanxiao Wang, Venkatesh Saligrama, Stan Sclaroff, Vitaly Ablavsky:
Cost-Aware Fine-Grained Recognition for IoTs Based on Sequential Fixations. ICCV 2019: 1252-1261 - [c126]Andrea Burns, Reuben Tan, Kate Saenko, Stan Sclaroff, Bryan A. Plummer:
Language Features Matter: Effective Language Representations for Vision-Language Tasks. ICCV 2019: 7473-7482 - [c125]Kuniaki Saito, Donghyun Kim, Stan Sclaroff, Trevor Darrell, Kate Saenko:
Semi-Supervised Domain Adaptation via Minimax Entropy. ICCV 2019: 8049-8057 - [c124]Sobhan Naderi Parizi, Kun He, Reza Aghajani, Stan Sclaroff, Pedro F. Felzenszwalb:
Generalized Majorization-Minimization. ICML 2019: 5022-5031 - [i30]Kuniaki Saito, Donghyun Kim, Stan Sclaroff, Trevor Darrell, Kate Saenko:
Semi-supervised Domain Adaptation via Minimax Entropy. CoRR abs/1904.06487 (2019) - [i29]Donghyun Kim, Sarah Adel Bargal, Jianming Zhang, Stan Sclaroff:
Multi-way Encoding for Robustness. CoRR abs/1906.02033 (2019) - [i28]Ping Hu, Ximeng Sun, Kate Saenko, Stan Sclaroff:
Weakly-supervised Compositional FeatureAggregation for Few-shot Recognition. CoRR abs/1906.04833 (2019) - [i27]Qi Feng, Vitaly Ablavsky, Qinxun Bai, Guorong Li, Stan Sclaroff:
Tell Me What to Track. CoRR abs/1907.11751 (2019) - [i26]Andrea Burns, Reuben Tan, Kate Saenko, Stan Sclaroff, Bryan A. Plummer:
Language Features Matter: Effective Language Representations for Vision-Language Tasks. CoRR abs/1908.06327 (2019) - [i25]Donghyun Kim, Kuniaki Saito, Kate Saenko, Stan Sclaroff, Bryan A. Plummer:
MULE: Multimodal Universal Language Embedding. CoRR abs/1909.03493 (2019) - [i24]Qi Feng, Vitaly Ablavsky, Qinxun Bai, Stan Sclaroff:
Robust Visual Object Tracking with Natural Language Region Proposal Network. CoRR abs/1912.02048 (2019) - [i23]Nuno C. Garcia, Sarah Adel Bargal, Vitaly Ablavsky, Pietro Morerio, Vittorio Murino, Stan Sclaroff:
DMCL: Distillation Multiple Choice Learning for Multimodal Action Recognition. CoRR abs/1912.10982 (2019) - 2018
- [j45]Shugao Ma, Jianming Zhang, Stan Sclaroff, Nazli Ikizler-Cinbis, Leonid Sigal:
Space-Time Tree Ensemble for Action Recognition and Localization. Int. J. Comput. Vis. 126(2-4): 314-332 (2018) - [j44]Danna Gurari, Kun He, Bo Xiong, Jianming Zhang, Mehrnoosh Sameki, Suyog Dutt Jain, Stan Sclaroff, Margrit Betke, Kristen Grauman:
Predicting Foreground Object Ambiguity and Efficiently Crowdsourcing the Segmentation(s). Int. J. Comput. Vis. 126(7): 714-730 (2018) - [j43]Jianming Zhang, Sarah Adel Bargal, Zhe Lin, Jonathan Brandt, Xiaohui Shen, Stan Sclaroff:
Top-Down Neural Attention by Excitation Backprop. Int. J. Comput. Vis. 126(10): 1084-1102 (2018) - [c123]Kun He, Yan Lu, Stan Sclaroff:
Local Descriptors Optimized for Average Precision. CVPR 2018: 596-605 - [c122]Sarah Adel Bargal, Andrea Zunino, Donghyun Kim, Jianming Zhang, Vittorio Murino, Stan Sclaroff:
Excitation Backprop for RNNs. CVPR 2018: 1440-1449 - [c121]Kun He, Fatih Çakir, Sarah Adel Bargal, Stan Sclaroff:
Hashing as Tie-Aware Learning to Rank. CVPR 2018: 4023-4032 - [c120]Fatih Çakir, Kun He, Stan Sclaroff:
Hashing with Binary Matrix Pursuit. ECCV (5) 2018: 344-361 - [c119]Ajjen Joshi, Soumya Ghosh, Sarah Gunnery, Linda Tickle-Degnen, Stan Sclaroff, Margrit Betke:
Context-Sensitive Prediction of Facial Expressivity Using Multimodal Hierarchical Bayesian Neural Networks. FG 2018: 278-285 - [i22]Fatih Çakir, Kun He, Sarah Adel Bargal, Stan Sclaroff:
Hashing with Mutual Information. CoRR abs/1803.00974 (2018) - [i21]Huijuan Xu, Kun He, Leonid Sigal, Stan Sclaroff, Kate Saenko:
Text-to-Clip Video Retrieval with Early Fusion and Re-Captioning. CoRR abs/1804.05113 (2018) - [i20]Kun He, Yan Lu, Stan Sclaroff:
Local Descriptors Optimized for Average Precision. CoRR abs/1804.05312 (2018) - [i19]Andrea Zunino, Sarah Adel Bargal, Pietro Morerio, Jianming Zhang, Stan Sclaroff, Vittorio Murino:
Excitation Dropout: Encouraging Plasticity in Deep Neural Networks. CoRR abs/1805.09092 (2018) - [i18]Fatih Çakir, Kun He, Stan Sclaroff:
Hashing with Binary Matrix Pursuit. CoRR abs/1808.01990 (2018) - [i17]Hanxiao Wang, Venkatesh Saligrama, Stan Sclaroff, Vitaly Ablavsky:
Learning Where to Fixate on Foveated Images. CoRR abs/1811.06868 (2018) - [i16]Bryan A. Plummer, Kevin J. Shih, Yichen Li, Ke Xu, Svetlana Lazebnik, Stan Sclaroff, Kate Saenko:
Open-vocabulary Phrase Detection. CoRR abs/1811.07212 (2018) - [i15]Sarah Adel Bargal, Andrea Zunino, Vitali Petsiuk, Jianming Zhang, Kate Saenko, Vittorio Murino, Stan Sclaroff:
Guided Zoom: Questioning Network Evidence for Fine-grained Classification. CoRR abs/1812.02626 (2018) - 2017
- [j42]Fatih Çakir, Sarah Adel Bargal, Stan Sclaroff:
Online supervised hashing. Comput. Vis. Image Underst. 156: 162-173 (2017) - [j41]Jianming Zhang, Shugao Ma, Mehrnoosh Sameki, Stan Sclaroff, Margrit Betke, Zhe Lin, Xiaohui Shen, Brian L. Price, Radomír Mech:
Salient Object Subitizing. Int. J. Comput. Vis. 124(2): 169-186 (2017) - [j40]Ajjen Joshi, Camille Monnier, Margrit Betke, Stan Sclaroff:
Comparing random forest approaches to segmenting and classifying gestures. Image Vis. Comput. 58: 86-95 (2017) - [j39]Shugao Ma, Sarah Adel Bargal, Jianming Zhang, Leonid Sigal, Stan Sclaroff:
Do less and achieve more: Training CNNs for action recognition utilizing action images from the Web. Pattern Recognit. 68: 334-345 (2017) - [c118]Ajjen Joshi, Soumya Ghosh, Margrit Betke, Stan Sclaroff, Hanspeter Pfister:
Personalizing Gesture Recognition Using Hierarchical Bayesian Neural Networks. CVPR 2017: 455-464 - [c117]Filip Malmberg, Robin Strand, Jianming Zhang, Stan Sclaroff:
The Boolean Map Distance: Theory and Efficient Computation. DGCI 2017: 335-346 - [c116]Fatih Çakir, Kun He, Sarah Adel Bargal, Stan Sclaroff:
MIHash: Online Hashing with Mutual Information. ICCV 2017: 437-445 - [i14]Mikhail Breslav, Tyson L. Hedrick, Stan Sclaroff, Margrit Betke:
Automating Image Analysis by Annotating Landmarks with Deep Neural Networks. CoRR abs/1702.00583 (2017) - [i13]Fatih Çakir, Kun He, Sarah Adel Bargal, Stan Sclaroff:
MIHash: Online Hashing with Mutual Information. CoRR abs/1703.08919 (2017) - [i12]Danna Gurari, Kun He, Bo Xiong, Jianming Zhang, Mehrnoosh Sameki, Suyog Dutt Jain, Stan Sclaroff, Margrit Betke, Kristen Grauman:
Predicting Foreground Object Ambiguity and Efficiently Crowdsourcing the Segmentation(s). CoRR abs/1705.00366 (2017) - [i11]Kun He, Fatih Çakir, Sarah A. Bargal, Stan Sclaroff:
Hashing as Tie-Aware Learning to Rank. CoRR abs/1705.08562 (2017) - [i10]Sarah Adel Bargal, Andrea Zunino, Donghyun Kim, Jianming Zhang, Vittorio Murino, Stan Sclaroff:
Excitation Backprop for RNNs. CoRR abs/1711.06778 (2017) - 2016
- [j38]Antonio Hernández-Vela, Stan Sclaroff, Sergio Escalera:
Poselet-Based Contextual Rescoring for Human Pose Estimation via Pictorial Structures. Int. J. Comput. Vis. 118(1): 49-64 (2016) - [j37]Jianming Zhang, Stan Sclaroff:
Exploiting Surroundedness for Saliency Detection: A Boolean Map Approach. IEEE Trans. Pattern Anal. Mach. Intell. 38(5): 889-902 (2016) - [c115]Shugao Ma, Leonid Sigal, Stan Sclaroff:
Learning Activity Progression in LSTMs for Activity Detection and Early Detection. CVPR 2016: 1942-1950 - [c114]Jianming Zhang, Stan Sclaroff, Zhe Lin, Xiaohui Shen, Brian L. Price, Radomír Mech:
Unconstrained Salient Object Detection via Proposal Subset Optimization. CVPR 2016: 5733-5742 - [c113]Jianming Zhang, Zhe L. Lin, Jonathan Brandt, Xiaohui Shen, Stan Sclaroff:
Top-Down Neural Attention by Excitation Backprop. ECCV (4) 2016: 543-559 - [c112]Qinxun Bai, Steven Rosenberg, Zheng Wu, Stan Sclaroff:
Differential Geometric Regularization for Supervised Learning of Classifiers. ICML 2016: 1879-1888 - [c111]Mikhail Breslav, Tyson L. Hedrick, Stan Sclaroff, Margrit Betke:
Discovering useful parts for pose estimation in sparsely annotated datasets. WACV 2016: 1-9 - [i9]Mikhail Breslav, Tyson L. Hedrick, Stan Sclaroff, Margrit Betke:
Discovering Useful Parts for Pose Estimation in Sparsely Annotated Datasets. CoRR abs/1605.00707 (2016) - [i8]Jianming Zhang, Shugao Ma, Mehrnoosh Sameki, Stan Sclaroff, Margrit Betke, Zhe Lin, Xiaohui Shen, Brian L. Price, Radomír Mech:
Salient Object Subitizing. CoRR abs/1607.07525 (2016) - [i7]Jianming Zhang, Zhe Lin, Jonathan Brandt, Xiaohui Shen, Stan Sclaroff:
Top-down Neural Attention by Excitation Backprop. CoRR abs/1608.00507 (2016) - 2015
- [j36]Liliana Lo Presti, Marco La Cascia, Stan Sclaroff, Octavia I. Camps:
Hankelet-based dynamical systems modeling for 3D action recognition. Image Vis. Comput. 44: 29-43 (2015) - [j35]Hao Jiang, Tai-Peng Tian, Stan Sclaroff:
Scale and Rotation Invariant Matching Using Linearly Augmented Trees. IEEE Trans. Pattern Anal. Mach. Intell. 37(12): 2558-2572 (2015) - [c110]Jianming Zhang, Shugao Ma, Mehrnoosh Sameki, Stan Sclaroff, Margrit Betke, Zhe L. Lin, Xiaohui Shen, Brian L. Price, Radomír Mech:
Salient Object Subitizing. CVPR 2015: 4045-4054 - [c109]Shugao Ma, Leonid Sigal, Stan Sclaroff:
Space-time tree ensemble for action recognition. CVPR 2015: 5024-5032 - [c108]Ajjen Joshi, Camille Monnier, Margrit Betke, Stan Sclaroff:
A random forest approach to segmenting and classifying gestures. FG 2015: 1-7 - [c107]Fatih Çakir, Stan Sclaroff:
Adaptive Hashing for Fast Similarity Search. ICCV 2015: 1044-1052 - [c106]Jianming Zhang, Stan Sclaroff, Zhe L. Lin, Xiaohui Shen, Brian L. Price, Radomír Mech:
Minimum Barrier Salient Object Detection at 80 FPS. ICCV 2015: 1404-1412 - [c105]Fatih Çakir, Stan Sclaroff:
Online supervised hashing. ICIP 2015: 2606-2610 - [c104]Sarah Adel Bargal, Alexander Welles, Cliff R. Chan, Samuel Howes, Stan Sclaroff, Elizabeth Ragan, Courtney Johnson, Christopher J. Gill:
Image-based Ear Biometric Smartphone App for Patient Identification in Field Settings. VISAPP (3) 2015: 171-179 - [i6]Qinxun Bai, Steven Rosenberg, Stan Sclaroff:
A Differential Geometric Approach to Classification. CoRR abs/1503.01436 (2015) - [i5]Sobhan Naderi Parizi, Kun He, Stan Sclaroff, Pedro F. Felzenszwalb:
Generalized Majorization-Minimization. CoRR abs/1506.07613 (2015) - [i4]Qinxun Bai, Henry Lam, Stan Sclaroff:
A Bayesian Approach for Online Classifier Ensemble. CoRR abs/1507.02011 (2015) - [i3]Fatih Çakir, Sarah Adel Bargal, Stan Sclaroff:
Online Supervised Hashing for Ever-Growing Datasets. CoRR abs/1511.03257 (2015) - [i2]Shugao Ma, Sarah Adel Bargal, Jianming Zhang, Leonid Sigal, Stan Sclaroff:
Do Less and Achieve More: Training CNNs for Action Recognition Utilizing Action Images from the Web. CoRR abs/1512.07155 (2015) - 2014
- [j34]Qiang Ji, Stan Sclaroff, Lijun Yin:
Best of Automatic Face and Gesture Recognition 2013. Image Vis. Comput. 32(10): 629 (2014) - [c103]Liliana Lo Presti, Marco La Cascia, Stan Sclaroff, Octavia I. Camps:
Gesture Modeling by Hanklet-Based Hidden Markov Model. ACCV (3) 2014: 529-546 - [c102]Antonio Hernández-Vela, Sergio Escalera, Stan Sclaroff:
Contextual Rescoring for Human Pose Estimation. BMVC 2014 - [c101]Svebor Karaman, Lorenzo Seidenari, Shugao Ma, Alberto Del Bimbo, Stan Sclaroff:
Adaptive Structured Pooling for Action Recognition. BMVC 2014 - [c100]Jianming Zhang, Shugao Ma, Stan Sclaroff:
MEEM: Robust Tracking via Multiple Experts Using Entropy Minimization. ECCV (6) 2014: 188-203 - [c99]Kun He, Leonid Sigal, Stan Sclaroff:
Parameterizing Object Detectors in the Continuous Pose Space. ECCV (4) 2014: 450-465 - [c98]Qinxun Bai, Henry Lam, Stan Sclaroff:
A Bayesian Framework for Online Classifier Ensemble. ICML 2014: 1584-1592 - [c97]Fatih Çakir, Stan Sclaroff:
Supervised hashing with error correcting codes. ACM Multimedia 2014: 785-788 - [c96]Mikhail Breslav, Nathan W. Fuller, Stan Sclaroff, Margrit Betke:
3D pose estimation of bats in the wild. WACV 2014: 91-98 - [i1]Fatih Çakir, Stan Sclaroff:
Visual Word Selection without Re-Coding and Re-Pooling. CoRR abs/1407.6174 (2014) - 2013
- [j33]Javier-Flavio Vigueras Gomez, Stan Sclaroff:
Fast vision-based scene modeling for augmented reality in unprepared man-made environments. J. Ambient Intell. Smart Environ. 5(5): 525-537 (2013) - [c95]James M. Rehg, Gregory D. Abowd, Agata Rozga, Mario Romero, Mark A. Clements, Stan Sclaroff, Irfan A. Essa, Opal Y. Ousley, Yin Li, Chanho Kim, Hrishikesh Rao, Jonathan C. Kim, Liliana Lo Presti, Jianming Zhang, Denis Lantsman, Jonathan Bidwell, Zhefan Ye:
Decoding Children's Social Behavior. CVPR 2013: 3414-3421 - [c94]Jianming Zhang, Stan Sclaroff:
Saliency Detection: A Boolean Map Approach. ICCV 2013: 153-160 - [c93]Qinxun Bai, Zheng Wu, Stan Sclaroff, Margrit Betke, Camille Monnier:
Randomized Ensemble Tracking. ICCV 2013: 2040-2047 - [c92]Shugao Ma, Jianming Zhang, Nazli Ikizler-Cinbis, Stan Sclaroff:
Action Recognition and Localization by Hierarchical Space-Time Segments. ICCV 2013: 2744-2751 - [c91]Liliana Lo Presti, Stan Sclaroff, Agata Rozga:
Joint Alignment and Modeling of Correlated Behavior Streams. ICCV Workshops 2013: 730-737 - [c90]Sergio Escalera, Jordi Gonzàlez, Xavier Baró, Miguel Reyes, Isabelle Guyon, Vassilis Athitsos, Hugo Jair Escalante, Leonid Sigal, Antonis A. Argyros, Cristian Sminchisescu, Richard Bowden, Stan Sclaroff:
ChaLearn multi-modal gesture recognition 2013: grand challenge and workshop summary. ICMI 2013: 365-368 - 2012
- [j32]Rui Li, Tai-Peng Tian, Stan Sclaroff:
Divide, Conquer and Coordinate: Globally Coordinated Switching Linear Dynamical System. IEEE Trans. Pattern Anal. Mach. Intell. 34(4): 654-669 (2012) - [j31]Liliana Lo Presti, Stan Sclaroff, Marco La Cascia:
Path Modeling and Retrieval in Distributed Video Surveillance Databases. IEEE Trans. Multim. 14(2): 346-360 (2012) - [j30]Nazli Ikizler-Cinbis, Stan Sclaroff:
Web-Based Classifiers for Human Action Recognition. IEEE Trans. Multim. 14(4): 1031-1045 (2012) - [j29]Ugur Murat Erdem, Stan Sclaroff:
Event prediction in a hybrid camera network. ACM Trans. Sens. Networks 8(2): 16:1-16:27 (2012) - [c89]Jianming Zhang, Liliana Lo Presti, Stan Sclaroff:
Online Multi-person Tracking by Tracker Hierarchy. AVSS 2012: 379-385 - [c88]Stan Sclaroff:
People in Motion: Pose, Action and Communication. BMVC 2012: 1 - [c87]Hao Jiang, Tai-Peng Tian, Kun He, Stan Sclaroff:
Scale resilient, rotation invariant articulated object matching. CVPR 2012: 143-150 - [c86]Zheng Wu, Ashwin Thangali, Stan Sclaroff, Margrit Betke:
Coupling detection and data association for multiple object tracking. CVPR 2012: 1948-1955 - [c85]Ramazan Gokberk Cinbis, Stan Sclaroff:
Contextual Object Detection Using Set-Based Classification. ECCV (6) 2012: 43-57 - [c84]Shugao Ma, Stan Sclaroff, Nazli Ikizler-Cinbis:
Unsupervised Learning of Discriminative Relative Visual Attributes. ECCV Workshops (3) 2012: 61-70 - [c83]Zoya Gavrilov, Stan Sclaroff, Carol Neidle, Sven J. Dickinson:
Detecting Reduplication in Videos of American Sign Language. LREC 2012: 3767-3773 - 2011
- [j28]Quan Yuan, Ashwin Thangali, Vitaly Ablavsky, Stan Sclaroff:
Learning a Family of Detectors via Multiplicative Kernels. IEEE Trans. Pattern Anal. Mach. Intell. 33(3): 514-530 (2011) - [j27]Vitaly Ablavsky, Stan Sclaroff:
Layered Graphical Models for Tracking Partially Occluded Objects. IEEE Trans. Pattern Anal. Mach. Intell. 33(9): 1758-1775 (2011) - [c82]Ashwin Thangali, Joan P. Nash, Stan Sclaroff, Carol Neidle:
Exploiting phonological constraints for handshape inference in ASL video. CVPR 2011: 521-528 - [c81]Hao Jiang, Tai-Peng Tian, Stan Sclaroff:
Scale and rotation invariant matching using linearly augmented trees. CVPR 2011: 2473-2480 - [c80]Vitaly Ablavsky, Stan Sclaroff:
Learning parameterized histogram kernels on the simplex manifold for image and action classification. ICCV 2011: 1473-1480 - [c79]Javier-Flavio Vigueras Gomez, Stan Sclaroff:
Real-time structure and motion recovery from two views of a multiplanar scene. ICCV Workshops 2011: 725-728 - 2010
- [j26]Rui Li, Tai-Peng Tian, Stan Sclaroff, Ming-Hsuan Yang:
3D Human Motion Tracking with a Coordinated Mixture of Factor Analyzers. Int. J. Comput. Vis. 87(1-2): 170-190 (2010) - [j25]Walter Nunziati, Stan Sclaroff, Alberto Del Bimbo:
Matching Trajectories between Video Sequences by Exploiting a Sparse Projective Invariant Representation. IEEE Trans. Pattern Anal. Mach. Intell. 32(3): 517-529 (2010) - [c78]Tai-Peng Tian, Stan Sclaroff:
Fast globally optimal 2D human detection with loopy graph models. CVPR 2010: 81-88 - [c77]Tai-Peng Tian, Stan Sclaroff:
Fast Multi-aspect 2D Human Detection. ECCV (3) 2010: 453-466 - [c76]Nazli Ikizler-Cinbis, Stan Sclaroff:
Object, Scene and Actions: Combining Multiple Features for Human Action Recognition. ECCV (1) 2010: 494-507 - [c75]Nazli Ikizler-Cinbis, Stan Sclaroff:
Object Recognition and Localization Via Spatial Instance Embedding. ICPR 2010: 452-455
2000 – 2009
- 2009
- [j24]Panagiotis Papapetrou, George Kollios, Stan Sclaroff, Dimitrios Gunopulos:
Mining frequent arrangements of temporal intervals. Knowl. Inf. Syst. 21(2): 133-171 (2009) - [j23]Hee-Deok Yang, Stan Sclaroff, Seong-Whan Lee:
Sign Language Spotting with a Threshold Model Based on Conditional Random Fields. IEEE Trans. Pattern Anal. Mach. Intell. 31(7): 1264-1277 (2009) - [j22]Jonathan Alon, Vassilis Athitsos, Quan Yuan, Stan Sclaroff:
A Unified Framework for Gesture Recognition and Spatiotemporal Gesture Segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 31(9): 1685-1699 (2009) - [c74]Ashwin Thangali, Stan Sclaroff:
An alignment based similarity measure for hand detection in cluttered sign language video. CVPR Workshops 2009: 89-96 - [c73]Alexandra Stefan, Vassilis Athitsos, Quan Yuan, Stan Sclaroff:
Reducing JointBoost-based multiclass classification to proximity search. CVPR 2009: 589-596 - [c72]Nazli Ikizler-Cinbis, Ramazan Gokberk Cinbis, Stan Sclaroff:
Learning actions from the Web. ICCV 2009: 995-1002 - [c71]Quan Yuan, Stan Sclaroff:
Is a detector only good for detection? ICCV 2009: 1066-1073 - [c70]Liliana Lo Presti, Stan Sclaroff, Marco La Cascia:
Object Matching in Distributed Video Surveillance Systems by LDA-Based Appearance Descriptors. ICIAP 2009: 547-557 - 2008
- [j21]Rui Li, Stan Sclaroff:
Multi-scale 3D scene flow from binocular stereo sequences. Comput. Vis. Image Underst. 110(1): 75-90 (2008) - [j20]Vassilis Athitsos, Jonathan Alon, Stan Sclaroff, George Kollios:
BoostMap: An Embedding Method for Efficient Nearest Neighbor Retrieval. IEEE Trans. Pattern Anal. Mach. Intell. 30(1): 89-104 (2008) - [j19]Jingbin Wang, Vassilis Athitsos, Stan Sclaroff, Margrit Betke:
Detecting Objects of Variable Shape Structure With Hidden State Shape Models. IEEE Trans. Pattern Anal. Mach. Intell. 30(3): 477-492 (2008) - [c69]Vitaly Ablavsky, Ashwin Thangali, Stan Sclaroff:
Layered graphical models for tracking partially-occluded objects. CVPR 2008 - [c68]Vassilis Athitsos, Carol Neidle, Stan Sclaroff, Joan P. Nash, Alexandra Stefan, Quan Yuan, Ashwin Thangali:
The American Sign Language Lexicon Video Dataset. CVPR Workshops 2008: 1-8 - [c67]Quan Yuan, Ashwin Thangali, Vitaly Ablavsky, Stan Sclaroff:
Multiplicative kernels: Object detection, segmentation and pose estimation. CVPR 2008 - [c66]Zheng Wu, Margrit Betke, Jingbin Wang, Vassilis Athitsos, Stan Sclaroff:
Tracking with Dynamic Hidden-State Shape Models. ECCV (1) 2008: 643-656 - [c65]Philippe Dreuw, Carol Neidle, Vassilis Athitsos, Stan Sclaroff, Hermann Ney:
Benchmark Databases for Video-Based Automatic Sign Language Recognition. LREC 2008 - [c64]Alexandra Stefan, Vassilis Athitsos, Jonathan Alon, Stan Sclaroff:
Translation and scale-invariant gesture recognition in complex scenes. PETRA 2008: 7 - 2007
- [j18]Vassilis Athitsos, Marios Hadjieleftheriou, George Kollios, Stan Sclaroff:
Query-sensitive embeddings. ACM Trans. Database Syst. 32(2): 8 (2007) - [c63]Quan Yuan, Ashwin Thangali, Vitaly Ablavsky, Stan Sclaroff:
Parameter Sensitive Detectors. CVPR 2007 - [c62]Vassilis Athitsos, Alexandra Stefan, Quan Yuan, Stan Sclaroff:
ClassMap: Efficient Multiclass Recognition via Embeddings. ICCV 2007: 1-8 - [c61]Rui Li, Tai-Peng Tian, Stan Sclaroff:
Simultaneous Learning of Nonlinear Manifold and Dynamical Models for High-dimensional Time Series. ICCV 2007: 1-8 - 2006
- [j17]Ugur Murat Erdem, Stan Sclaroff:
Automated camera layout to satisfy task-specific and floor plan-specific coverage requirements. Comput. Vis. Image Underst. 103(3): 156-169 (2006) - [j16]Rómer Rosales, Stan Sclaroff:
Combining Generative and Discriminative Models in a Framework for Articulated Pose Estimation. Int. J. Comput. Vis. 67(3): 251-276 (2006) - [c60]Vassilis Athitsos, Jingbin Wang, Stan Sclaroff, Margrit Betke:
Detecting Instances of Shape Classes That Exhibit Variable Structure. ECCV (1) 2006: 121-134 - [c59]Rui Li, Ming-Hsuan Yang, Stan Sclaroff, Tai-Peng Tian:
Monocular Tracking of 3D Human Motion with a Coordinated Mixture of Factor Analyzers. ECCV (2) 2006: 137-150 - 2005
- [c58]Walter Nunziati, Jonathan Alon, Stan Sclaroff, Alberto Del Bimbo:
View registration using interesting segments of planar trajectories. AVSS 2005: 75-80 - [c57]Ugur Murat Erdem, Stan Sclaroff:
Look there! Predicting where to look for motion in an active camera network. AVSS 2005: 105-110 - [c56]Walter Nunziati, Stan Sclaroff, Alberto Del Bimbo:
An Invariant Representation for Matching Trajectories Across Uncalibrated Video Streams. CIVR 2005: 318-327 - [c55]Vassilis Athitsos, Stan Sclaroff:
Boosting nearest neighbor classifiers for multiclass recognition. CVPR Workshops 2005: 45 - [c54]Tai-Peng Tian, Rui Li, Stan Sclaroff:
Articulated Pose Estimation in a Learned Smooth Space of Feasible Solutions. CVPR Workshops 2005: 50 - [c53]Quan Yuan, Ashwin Thangali, Stan Sclaroff:
Face Identification by a Cascade of Rejection Classifiers. CVPR Workshops 2005: 152 - [c52]Vassilis Athitsos, Jonathan Alon, Stan Sclaroff:
Efficient Nearest Neighbor Classification Using a Cascade of Approximate Similarity Measures. CVPR (1) 2005: 486-493 - [c51]Jonathan Alon, Vassilis Athitsos, Stan Sclaroff:
Accurate and Efficient Gesture Spotting via Pruning and Subgesture Reasoning. ICCV-HCI 2005: 189-198 - [c50]Stan Sclaroff, Margrit Betke, George Kollios, Jonathan Alon, Vassilis Athitsos, Rui Li, John J. Magee, Tai-Peng Tian:
Tracking, Analysis, and Recognition of Human Gestures in Video. ICDAR 2005: 806-810 - [c49]Jonathan Alon, Vassilis Athitsos, Stan Sclaroff:
Online and Offline Character Recognition Using Alignment to Prototypes. ICDAR 2005: 839-845 - [c48]Panagiotis Papapetrou, George Kollios, Stan Sclaroff, Dimitrios Gunopulos:
Discovering Frequent Arrangements of Temporal Intervals. ICDM 2005: 354-361 - [c47]Vassilis Athitsos, Marios Hadjieleftheriou, George Kollios, Stan Sclaroff:
Query-Sensitive Embeddings. SIGMOD Conference 2005: 706-717 - [c46]Rui Li, Stan Sclaroff:
Multi-Scale 3D Scene Flow from Binocular Stereo Sequences. WACV/MOTION 2005: 147-153 - [c45]Ashwin Thangali, Stan Sclaroff:
Periodic Motion Detection and Estimation via Space-Time Sampling. WACV/MOTION 2005: 176-182 - [c44]Tai-Peng Tian, Stan Sclaroff:
Handsignals Recognition From Video Using 3D Motion Capture Data. WACV/MOTION 2005: 189-194 - [c43]Quan Yuan, Stan Sclaroff, Vassilis Athitsos:
Automatic 2D Hand Tracking in Video Sequences. WACV/MOTION 2005: 250-256 - [c42]Jonathan Alon, Vassilis Athitsos, Quan Yuan, Stan Sclaroff:
Simultaneous Localization and Recognition of Dynamic Hand Gestures. WACV/MOTION 2005: 254-260 - 2004
- [j15]Lifeng Liu, Stan Sclaroff:
Deformable model-guided region split and merge of image regions. Image Vis. Comput. 22(4): 343-354 (2004) - [j14]Leonid Sigal, Stan Sclaroff, Vassilis Athitsos:
Skin Color-Based Video Segmentation under Time-Varying Illumination. IEEE Trans. Pattern Anal. Mach. Intell. 26(7): 862-877 (2004) - [c41]Vassilis Athitsos, Jonathan Alon, Stan Sclaroff, George Kollios:
BoostMap: A Method for Efficient Approximate Similarity Rankings. CVPR (2) 2004: 268-275 - [c40]Dan Buzan, Stan Sclaroff, George Kollios:
Extraction and Clustering of Motion Trajectories in Video. ICPR (2) 2004: 521-524 - [c39]Marco La Cascia, Lorenzo Valenti, Stan Sclaroff:
Fully automatic, real-time detection of facial gestures from generic video. MMSP 2004: 175-178 - 2003
- [j13]Stan Sclaroff, John Isidoro:
Active blobs: region-based, deformable appearance models. Comput. Vis. Image Underst. 89(2-3): 197-225 (2003) - [j12]Rómer Rosales, Stan Sclaroff:
A framework for heading-guided recognition of human activity. Comput. Vis. Image Underst. 91(3): 335-367 (2003) - [c38]Jonathan Alon, Stan Sclaroff, George Kollios, Vladimir Pavlovic:
Discovering Clusters in Motion Time-Series Data. CVPR (1) 2003: 375-381 - [c37]Vassilis Athitsos, Stan Sclaroff:
Estimating 3D Hand Pose from a Cluttered Image. CVPR (2) 2003: 432-442 - [c36]Vassilis Athitsos, Stan Sclaroff:
Database Indexing Methods for 3D Hand Pose Estimation. Gesture Workshop 2003: 288-299 - [c35]Jing Zhong, Stan Sclaroff:
Segmenting Foreground Objects from a Dynamic Textured Background via a Robust Kalman Filter. ICCV 2003: 44-50 - [c34]John Isidoro, Stan Sclaroff:
Stochastic Refinement of the Visual Hull to Satisfy Photometric and Silhouette Consistency Constraints. ICCV 2003: 1335-1342 - 2002
- [j11]Lifeng Liu, Stan Sclaroff:
Index trees for accelerating deformable template matching. Pattern Recognit. Lett. 23(12): 1483-1493 (2002) - [c33]Matheen Siddiqui, Stan Sclaroff:
Surface Reconstruction from Multiple Views using Rational B-Splines and Knot Insertion. 3DPVT 2002: 372-379 - [c32]John Isidoro, Stan Sclaroff:
Stochastic Mesh-Based Multiview Reconstruction. 3DPVT 2002: 568-577 - [c31]Vassilis Athitsos, Stan Sclaroff:
An Appearance-Based Framework for 3D Hand Shape Classification and Camera Viewpoint Estimation. FGR 2002: 45-52 - [c30]Rómer Rosales, Stan Sclaroff:
Algorithms for Inference in Specialized Maps for Recovering 3D Hand Pose. FGR 2002: 143-148 - [c29]Ugur Murat Erdem, Stan Sclaroff:
Automatic Detection of Relevant Head Gestures in American Sign Language Communication. ICPR (1) 2002: 460- - 2001
- [j10]Stan Sclaroff, Lifeng Liu:
Deformable Shape Detection and Description via Model-Based Region Grouping. IEEE Trans. Pattern Anal. Mach. Intell. 23(5): 475-489 (2001) - [j9]Stan Sclaroff, Lifeng Liu:
Corrections to 'Deformable Shape Detection and Description via Model-Based Region Grouping'. IEEE Trans. Pattern Anal. Mach. Intell. 23(6): 685 (2001) - [c28]Rómer Rosales, Matheen Siddiqui, Jonathan Alon, Stan Sclaroff:
Estimating 3D Body Pose using Uncalibrated Cameras. CVPR (1) 2001: 821-827 - [c27]George Kollios, Stan Sclaroff, Margrit Betke:
Motion Mining: Discovering Spatio-Temporal Patterns in Databases of Human Motion. DMKD 2001 - [c26]Lifeng Liu, Stan Sclaroff:
Region Segmentation via Deformable Model-Guided Split and Merge. ICCV 2001: 98-104 - [c25]Rómer Rosales, Vassilis Athitsos, Leonid Sigal, Stan Sclaroff:
3D Hand Pose Reconstruction Using Specialized Mappings. ICCV 2001: 378-387 - [c24]Lifeng Liu, Stan Sclaroff:
Medical image segmentation and retrieval via deformable models. ICIP (3) 2001: 1071-1074 - [c23]Lifeng Liu, Stan Sclaroff:
Shape-Guided Split and Merge of Image Regions. IWVF 2001: 367-377 - [c22]Stan Sclaroff, George Kollios, Margrit Betke, Rómer Rosales:
Motion Mining. MDIC 2001: 16-32 - [c21]Rómer Rosales, Stan Sclaroff:
Learning Body Pose via Specialized Maps. NIPS 2001: 1263-1270 - [p2]Stan Sclaroff, Marco La Cascia, Saratendu Sethi, Leonid Taycher:
Mix and Match Features in the ImageRover Search Engine. Principles of Visual Information Retrieval 2001: 259-277 - 2000
- [j8]Marco La Cascia, Stan Sclaroff, Vassilis Athitsos:
Fast, Reliable Head Tracking under Varying Illumination: An Approach Based on Registration of Texture-Mapped 3D Models. IEEE Trans. Pattern Anal. Mach. Intell. 22(4): 322-336 (2000) - [c20]Leonid Sigal, Stan Sclaroff, Vassilis Athitsos:
Estimation and Prediction of Evolving Color Distributions for Skin Segmentation under Varying Illumination. CVPR 2000: 2152-2159 - [c19]Jonathan Alon, Stan Sclaroff:
Recursive Estimation of Motion and Planar Structure. CVPR 2000: 2550-2556 - [c18]Rómer Rosales, Stan Sclaroff:
Inferring Body Pose without Tracking Body Parts. CVPR 2000: 2721- - [c17]Rómer Rosales, Stan Sclaroff:
Learning and Synthesizing Human Body Motion and Posture. FG 2000: 506-511 - [c16]Rómer Rosales, Stan Sclaroff:
Specialized Mappings and the Estimation of Human Body Pose from a Single Image. Workshop on Human Motion 2000: 19-24
1990 – 1999
- 1999
- [j7]Stan Sclaroff, Marco La Cascia, Saratendu Sethi, Leonid Taycher:
Unifying Textual and Visual Cues for Content-Based Image Retrieval on the World Wide Web. Comput. Vis. Image Underst. 75(1-2): 86-98 (1999) - [c15]Marco La Cascia, Stan Sclaroff:
Fast, Reliable Head Tracking under Varying Illumination. CVPR 1999: 1604-1610 - [c14]Lifeng Liu, Stan Sclaroff:
Deformable Shape Detection and Description via Model-Based Region. CVPR 1999: 2021-2027 - [c13]Rómer Rosales, Stan Sclaroff:
3D Trajectory Recovery for Tracking Multiple Objects and Trajectory Guided Recognition of Actions. CVPR 1999: 2117-2123 - [c12]Lifeng Liu, Stan Sclaroff:
Automatic Deformable Shape Segmentation for Image Database Search Applications. VISUAL 1999: 601-608 - 1998
- [j6]John Martin, Alex Pentland, Stan Sclaroff, Ron Kikinis:
Characterization of Neuropathological Shape Deformations. IEEE Trans. Pattern Anal. Mach. Intell. 20(2): 97-112 (1998) - [c11]John Isidoro, Stan Sclaroff:
Active Voodoo Dolls: A Vision Based Input Device for Nonrigid Control. CA 1998: 137-143 - [c10]Marco La Cascia, John Isidoro, Stan Sclaroff:
Head Tracking via Robust Registration in Texture Map Images. CVPR 1998: 508-514 - [c9]Stan Sclaroff, John Isidoro:
Active Blobs. ICCV 1998: 1146-1153 - [p1]Stan Sclaroff:
Distance to Deformable Prototypes: Encoding Shape Categories for Efficient Search. Image Databases and Multi-Media Search 1998: 149-164 - 1997
- [j5]Stan Sclaroff:
Deformable prototypes for encoding shape categories in image databases. Pattern Recognit. 30(4): 627-641 (1997) - 1996
- [j4]Alex Pentland, Rosalind W. Picard, Stan Sclaroff:
Photobook: Content-based manipulation of image databases. Int. J. Comput. Vis. 18(3): 233-254 (1996) - 1995
- [j3]Stan Sclaroff, Alex Pentland:
Modal Matching for Correspondence and Recognition. IEEE Trans. Pattern Anal. Mach. Intell. 17(6): 545-561 (1995) - 1994
- [c8]Alex Pentland, Trevor Darrell, Irfan A. Essa, Ali Azarbayejani, Stan Sclaroff:
Visually guided animation. CA 1994: 112-121 - [c7]Jean Ponce, Ruzena Bajcsy, Dimitris N. Metaxas, Thomas O. Binford, David A. Forsyth, Martial Hebert, Katsushi Ikeuchi, Avinash C. Kak, Linda G. Shapiro, Stan Sclaroff, Alex Pentland, George C. Stockman:
Object representation for object recognition. CVPR 1994: 147-152 - [c6]Alex Pentland, Stan Sclaroff:
Modal Representations. Object Representation in Computer Vision 1994: 249-262 - [c5]Alex Pentland, Rosalind W. Picard, Stan Sclaroff:
Photobook: Tools for Content-Based Manipulation of Image Databases. Storage and Retrieval for Image and Video Databases (SPIE) 1994: 34-47 - 1993
- [c4]Stan Sclaroff, Alex Pentland:
A modal framework for correspondence and description. ICCV 1993: 308-313 - 1992
- [j2]Irfan A. Essa, Stan Sclaroff, Alex Pentland:
A Unified Approach for Physical and Geometric Modeling for Graphics and Animation. Comput. Graph. Forum 11(3): 129-138 (1992) - 1991
- [j1]Alex Pentland, Stan Sclaroff:
Closed-Form Solutions for Physically Based Shape Modeling and Recognition. IEEE Trans. Pattern Anal. Mach. Intell. 13(7): 715-729 (1991) - [c3]Stan Sclaroff, Alex Pentland:
Closed-form solutions for physically-based shape modeling and recognition. CVPR 1991: 238-243 - [c2]Stan Sclaroff, Alex Pentland:
Generalized implicit functions for computer graphics. SIGGRAPH 1991: 247-250 - 1990
- [c1]Trevor Darrell, Stan Sclaroff, Alex Pentland:
Segmentation by minimal description. ICCV 1990: 112-116
Coauthor Index
Sarah Adel Bargal
aka: Sarah A. Bargal
aka: Sarah A. Bargal
[j55] [j54] [i55] [i54] [i53] [j52] [j51] [j50] [c157] [c155] [c154] [c152] [i52] [i51] [i50] [i48] [i47] [j48] [j47] [c151] [c147] [c146] [c145] [c144] [i43] [i42] [c141] [c138] [c137] [c136] [c133] [i39] [i37] [i36] [i35] [i32] [i31] [c132] [c131] [c130] [c126] [c125] [i30] [i28] [i26] [i25] [i21] [i16] [i15]
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