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ORCIDYi Zhu 0001
Person information
- affiliation: Amazon
- affiliation (PhD 2019): University of California, Merced, USA
Other persons with the same name
- Yi Zhu — disambiguation page
- Yi Zhu 0002 — University of California, San Diego, USA
- Yi Zhu 0003 — Delft University of Technology, Netherlands
- Yi Zhu 0004
![[0000-0002-5087-895X]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0002-5087-895X")
— Chinese Academy of Sciences, China - Yi Zhu 0005 — Hawaii Pacific University, Honolulu, HI, USA (and 1 more)
- Yi Zhu 0006 — Yangzhou University, Department of Computer Science, Yangzhou, China (and 1 more)
- Yi Zhu 0007 — Hong Kong University of Science Technology, Department of IEEM, Hong Kong
- Yi Zhu 0008 — Nanjing University of Aeronautics and Astronautics, College of Information Science and Technology, China
- Yi Zhu 0009 — Tianjin University, Tianjin Key Laboratory of Cognitive Computing and Application, College of Intelligence and Computing, China
- Yi Zhu 0010 — Tsinghua Unversity, Yau Mathematical Sciences Center, Beijing, China (and 1 more)
- Yi Zhu 0011 — University of Québec, Multisensory Signal Analysis and Enhancement Lab, MuSAE, National Institute of Scientific Research, INRS, Canada (and 1 more)
- Yi Zhu 0012 — State University of New York at Buffalo, Department of Computer Science and Engineering, Buffalo, NY, USA
- Yi Zhu 0013 — Jiangsu Normal University, School of Computer Science, Xuzhou, China (and 1 more)
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2020 – today
- 2024
[j5]Yi Zhu, Zhongyue Zhang, Chongruo Wu, Zhi Zhang, Tong He, Hang Zhang, R. Manmatha, Mu Li, Alexander J. Smola:
Improving Semantic Segmentation via Efficient Self-Training. IEEE Trans. Pattern Anal. Mach. Intell. 46(3): 1589-1602 (2024)- 2023
- [j4]Shengju Qian, Yi Zhu, Wenbo Li, Mu Li, Jiaya Jia:
What Makes for Good Tokenizers in Vision Transformer? IEEE Trans. Pattern Anal. Mach. Intell. 45(11): 13011-13023 (2023) - [c36]Yuxin Ren, Zihan Zhong, Xingjian Shi, Yi Zhu, Chun Yuan, Mu Li:
Tailoring Instructions to Student's Learning Levels Boosts Knowledge Distillation. ACL (1) 2023: 1990-2006 - [c35]Matías Mendieta, Boran Han, Xingjian Shi, Yi Zhu, Chen Chen:
Towards Geospatial Foundation Models via Continual Pretraining. ICCV 2023: 16760-16770 - [c34]Taojiannan Yang, Yi Zhu, Yusheng Xie, Aston Zhang, Chen Chen, Mu Li:
AIM: Adapting Image Models for Efficient Video Action Recognition. ICLR 2023 - [c33]Zhihan Gao, Xingjian Shi, Boran Han, Hao Wang, Xiaoyong Jin, Danielle C. Maddix, Yi Zhu, Mu Li, Yuyang Wang:
PreDiff: Precipitation Nowcasting with Latent Diffusion Models. NeurIPS 2023 - [c32]Shuhuai Ren, Aston Zhang, Yi Zhu, Shuai Zhang, Shuai Zheng, Mu Li, Alexander J. Smola, Xu Sun:
Prompt Pre-Training with Twenty-Thousand Classes for Open-Vocabulary Visual Recognition. NeurIPS 2023 - [c31]Xiaoshuai Hao, Yi Zhu, Srikar Appalaraju, Aston Zhang, Wanqian Zhang, Bo Li, Mu Li:
MixGen: A New Multi-Modal Data Augmentation. WACV (Workshops) 2023: 379-389 - [c30]Xuelin Qian, Li Wang, Yi Zhu, Li Zhang, Yanwei Fu, Xiangyang Xue:
ImpDet: Exploring Implicit Fields for 3D Object Detection. WACV 2023: 4249-4259 - [i49]Taojiannan Yang, Yi Zhu, Yusheng Xie, Aston Zhang, Chen Chen, Mu Li:
AIM: Adapting Image Models for Efficient Video Action Recognition. CoRR abs/2302.03024 (2023) - [i48]Yash Patel, Yusheng Xie, Yi Zhu, Srikar Appalaraju, R. Manmatha:
SimCon Loss with Multiple Views for Text Supervised Semantic Segmentation. CoRR abs/2302.03432 (2023) - [i47]Matías Mendieta, Boran Han, Xingjian Shi, Yi Zhu, Chen Chen, Mu Li:
GFM: Building Geospatial Foundation Models via Continual Pretraining. CoRR abs/2302.04476 (2023) - [i46]Shuhuai Ren, Aston Zhang, Yi Zhu, Shuai Zhang, Shuai Zheng, Mu Li, Alex Smola, Xu Sun:
Prompt Pre-Training with Twenty-Thousand Classes for Open-Vocabulary Visual Recognition. CoRR abs/2304.04704 (2023) - [i45]Yuxin Ren, Zihan Zhong, Xingjian Shi, Yi Zhu, Chun Yuan, Mu Li:
Tailoring Instructions to Student's Learning Levels Boosts Knowledge Distillation. CoRR abs/2305.09651 (2023) - [i44]Zhihan Gao, Xingjian Shi, Boran Han, Hao Wang, Xiaoyong Jin, Danielle C. Maddix, Yi Zhu, Mu Li, Yuyang Wang:
PreDiff: Precipitation Nowcasting with Latent Diffusion Models. CoRR abs/2307.10422 (2023) - 2022
- [j3]Song Peng, Zhenfeng Shao, Xiao Huang, Yi Zhu, Ruiqian Zhang, Junwei Zha:
BiCSNet: A Bidirectional Cross-Scale Backbone for Recognition and Localization. IEEE Trans. Circuits Syst. Video Technol. 32(8): 4940-4952 (2022) - [c29]Hang Zhang, Chongruo Wu, Zhongyue Zhang, Yi Zhu, Haibin Lin, Zhi Zhang, Yue Sun, Tong He, Jonas Mueller, R. Manmatha, Mu Li, Alexander J. Smola:
ResNeSt: Split-Attention Networks. CVPR Workshops 2022: 2735-2745 - [c28]Likun Cai, Zhi Zhang, Yi Zhu, Li Zhang, Mu Li, Xiangyang Xue:
BigDetection: A Large-scale Benchmark for Improved Object Detector Pre-training. CVPR Workshops 2022: 4776-4786 - [c27]Haotao Wang, Aston Zhang, Yi Zhu, Shuai Zheng, Mu Li, Alex J. Smola, Zhangyang Wang:
Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition. ICML 2022: 23446-23458 - [c26]Zhihan Gao, Xingjian Shi, Hao Wang, Yi Zhu, Yuyang Wang, Mu Li, Dit-Yan Yeung:
Earthformer: Exploring Space-Time Transformers for Earth System Forecasting. NeurIPS 2022 - [c25]Xinyu Li, Chunhui Liu, Bing Shuai, Yi Zhu, Hao Chen, Joseph Tighe:
NUTA: Non-uniform Temporal Aggregation for Action Recognition. WACV 2022: 827-836 - [i43]Likun Cai, Zhi Zhang, Yi Zhu, Li Zhang, Mu Li, Xiangyang Xue:
BigDetection: A Large-scale Benchmark for Improved Object Detector Pre-training. CoRR abs/2203.13249 (2022) - [i42]Xuelin Qian, Li Wang, Yi Zhu, Li Zhang, Yanwei Fu, Xiangyang Xue:
ImpDet: Exploring Implicit Fields for 3D Object Detection. CoRR abs/2203.17240 (2022) - [i41]Xiaoshuai Hao, Yi Zhu, Srikar Appalaraju, Aston Zhang, Wanqian Zhang, Bo Li, Mu Li:
MixGen: A New Multi-Modal Data Augmentation. CoRR abs/2206.08358 (2022) - [i40]Haotao Wang, Aston Zhang, Yi Zhu, Shuai Zheng, Mu Li, Alex Smola, Zhangyang Wang:
Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition. CoRR abs/2207.01160 (2022) - [i39]Zhihan Gao, Xingjian Shi, Hao Wang, Yi Zhu, Yuyang Wang, Mu Li, Dit-Yan Yeung:
Earthformer: Exploring Space-Time Transformers for Earth System Forecasting. CoRR abs/2207.05833 (2022) - [i38]Yunhe Gao, Xingjian Shi, Yi Zhu, Hao Wang, Zhiqiang Tang, Xiong Zhou, Mu Li, Dimitris N. Metaxas:
Visual Prompt Tuning for Test-time Domain Adaptation. CoRR abs/2210.04831 (2022) - [i37]Jielin Qiu, Yi Zhu, Xingjian Shi, Florian Wenzel, Zhiqiang Tang, Ding Zhao, Bo Li, Mu Li:
Are Multimodal Models Robust to Image and Text Perturbations? CoRR abs/2212.08044 (2022) - [i36]M. Saiful Bari, Aston Zhang, Shuai Zheng, Xingjian Shi, Yi Zhu, Shafiq Joty, Mu Li:
SPT: Semi-Parametric Prompt Tuning for Multitask Prompted Learning. CoRR abs/2212.10929 (2022) - [i35]Shengju Qian, Yi Zhu, Wenbo Li, Mu Li, Jiaya Jia:
What Makes for Good Tokenizers in Vision Transformer? CoRR abs/2212.11115 (2022) - 2021
- [c24]Zhiqiang Tang, Yunhe Gao, Yi Zhu, Zhi Zhang, Mu Li, Dimitris N. Metaxas:
CrossNorm and SelfNorm for Generalization under Distribution Shifts. ICCV 2021: 52-61 - [c23]Yanyi Zhang, Xinyu Li, Chunhui Liu, Bing Shuai, Yi Zhu, Biagio Brattoli, Hao Chen, Ivan Marsic, Joseph Tighe:
VidTr: Video Transformer Without Convolutions. ICCV 2021: 13557-13567 - [c22]Fangrui Zhu, Yi Zhu, Li Zhang, Chongruo Wu, Yanwei Fu, Mu Li:
A Unified Efficient Pyramid Transformer for Semantic Segmentation. ICCVW 2021: 2667-2677 - [c21]Haofei Kuang, Yi Zhu, Zhi Zhang, Xinyu Li, Joseph Tighe, Sören Schwertfeger, Cyrill Stachniss, Mu Li:
Video Contrastive Learning with Global Context. ICCVW 2021: 3188 - [c20]Shengju Qian, Hao Shao, Yi Zhu, Mu Li, Jiaya Jia:
Blending Anti-Aliasing into Vision Transformer. NeurIPS 2021: 5416-5429 - [c19]Li Wang, Li Zhang, Yi Zhu, Zhi Zhang, Tong He, Mu Li, Xiangyang Xue:
Progressive Coordinate Transforms for Monocular 3D Object Detection. NeurIPS 2021: 13364-13377 - [c18]Xueqing Deng, Yi Zhu, Yuxin Tian, Shawn D. Newsam:
Scale Aware Adaptation for Land-Cover Classification in Remote Sensing Imagery. WACV 2021: 2159-2168 - [i34]Zhiqiang Tang, Yunhe Gao, Yi Zhu, Zhi Zhang, Mu Li, Dimitris N. Metaxas:
SelfNorm and CrossNorm for Out-of-Distribution Robustness. CoRR abs/2102.02811 (2021) - [i33]Xinyu Li, Yanyi Zhang, Chunhui Liu, Bing Shuai, Yi Zhu, Biagio Brattoli, Hao Chen, Ivan Marsic, Joseph Tighe:
VidTr: Video Transformer Without Convolutions. CoRR abs/2104.11746 (2021) - [i32]Xueqing Deng, Yi Zhu, Yuxin Tian, Shawn D. Newsam:
AutoAdapt: Automated Segmentation Network Search for Unsupervised Domain Adaptation. CoRR abs/2106.13227 (2021) - [i31]Fangrui Zhu, Yi Zhu, Li Zhang, Chongruo Wu, Yanwei Fu, Mu Li:
A Unified Efficient Pyramid Transformer for Semantic Segmentation. CoRR abs/2107.14209 (2021) - [i30]Haofei Kuang, Yi Zhu, Zhi Zhang, Xinyu Li, Joseph Tighe, Sören Schwertfeger, Cyrill Stachniss, Mu Li:
Video Contrastive Learning with Global Context. CoRR abs/2108.02722 (2021) - [i29]Li Wang, Li Zhang, Yi Zhu, Zhi Zhang, Tong He, Mu Li, Xiangyang Xue:
Progressive Coordinate Transforms for Monocular 3D Object Detection. CoRR abs/2108.05793 (2021) - [i28]Shengju Qian, Hao Shao, Yi Zhu, Mu Li, Jiaya Jia:
Blending Anti-Aliasing into Vision Transformer. CoRR abs/2110.15156 (2021) - 2020
- [j2]Jian Guo, He He, Tong He, Leonard Lausen, Mu Li, Haibin Lin, Xingjian Shi, Chenguang Wang, Junyuan Xie, Sheng Zha, Aston Zhang, Hang Zhang, Zhi Zhang, Zhongyue Zhang, Shuai Zheng, Yi Zhu:
GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing. J. Mach. Learn. Res. 21: 23:1-23:7 (2020) - [c17]Yuxin Tian, Xueqing Deng, Yi Zhu, Shawn D. Newsam:
Cross-Time and Orientation-Invariant Overhead Image Geolocalization Using Deep Local Features. WACV 2020: 2501-2509 - [i27]Hang Zhang, Chongruo Wu, Zhongyue Zhang, Yi Zhu, Zhi Zhang, Haibin Lin, Yue Sun, Tong He, Jonas Mueller, R. Manmatha, Mu Li, Alexander J. Smola:
ResNeSt: Split-Attention Networks. CoRR abs/2004.08955 (2020) - [i26]Yi Zhu, Zhongyue Zhang, Chongruo Wu, Zhi Zhang, Tong He, Hang Zhang, R. Manmatha, Mu Li, Alexander J. Smola:
Improving Semantic Segmentation via Self-Training. CoRR abs/2004.14960 (2020) - [i25]Xueqing Deng, Yi Zhu, Yuxin Tian, Shawn D. Newsam:
Scale Aware Adaptation for Land-Cover Classification in Remote Sensing Imagery. CoRR abs/2012.04222 (2020) - [i24]Yi Zhu, Xinyu Li, Chunhui Liu, Mohammadreza Zolfaghari, Yuanjun Xiong, Chongruo Wu, Zhi Zhang, Joseph Tighe, R. Manmatha, Mu Li:
A Comprehensive Study of Deep Video Action Recognition. CoRR abs/2012.06567 (2020) - [i23]Xinyu Li, Chunhui Liu, Bing Shuai, Yi Zhu, Hao Chen, Joseph Tighe:
NUTA: Non-uniform Temporal Aggregation for Action Recognition. CoRR abs/2012.08041 (2020)
2010 – 2019
- 2019
- [b1]Yi Zhu:
Exploring Temporal Information for Improved Video Understanding. University of California, Merced, USA, 2019 - [j1]Yi Zhu, Xueqing Deng, Shawn D. Newsam:
Fine-Grained Land Use Classification at the City Scale Using Ground-Level Images. IEEE Trans. Multim. 21(7): 1825-1838 (2019) - [c16]Yi Zhu, Shawn D. Newsam:
Motion-Aware Feature for Improved Video Anomaly Detection. BMVC 2019: 270 - [c15]Yi Zhu, Karan Sapra, Fitsum A. Reda, Kevin J. Shih, Shawn D. Newsam, Andrew Tao, Bryan Catanzaro:
Improving Semantic Segmentation via Video Propagation and Label Relaxation. CVPR 2019: 8856-8865 - [i22]Xueqing Deng, Yi Zhu, Shawn D. Newsam:
Using Conditional Generative Adversarial Networks to Generate Ground-Level Views From Overhead Imagery. CoRR abs/1902.06923 (2019) - [i21]Yi Zhu:
Exploring Temporal Information for Improved Video Understanding. CoRR abs/1905.10654 (2019) - [i20]Yi Zhu, Shawn D. Newsam:
Motion-Aware Feature for Improved Video Anomaly Detection. CoRR abs/1907.10211 (2019) - [i19]Xueqing Deng, Yi Zhu, Yuxin Tian, Shawn D. Newsam:
Generalizing Deep Models for Overhead Image Segmentation Through Getis-Ord Gi* Pooling. CoRR abs/1912.10667 (2019) - 2018
- [c14]Yi Zhu, Jia Xue, Shawn D. Newsam:
Gated Transfer Network for Transfer Learning. ACCV (4) 2018: 354-369 - [c13]Yi Zhu, Zhen-Zhong Lan, Shawn D. Newsam, Alexander G. Hauptmann:
Hidden Two-Stream Convolutional Networks for Action Recognition. ACCV (3) 2018: 363-378 - [c12]Yi Zhu, Shawn D. Newsam:
Random Temporal Skipping for Multirate Video Analysis. ACCV (3) 2018: 542-557 - [c11]Yi Zhu, Yang Long, Yu Guan, Shawn D. Newsam, Ling Shao:
Towards Universal Representation for Unseen Action Recognition. CVPR 2018: 9436-9445 - [c10]Xueqing Deng, Yi Zhu, Shawn D. Newsam:
What is it like down there?: generating dense ground-level views and image features from overhead imagery using conditional generative adversarial networks. SIGSPATIAL/GIS 2018: 43-52 - [c9]Xueqing Deng, Yi Zhu, Shawn D. Newsam:
Spatial Morphing Kernel Regression for Feature Interpolation. ICIP 2018: 2182-2186 - [c8]Yi Zhu, Shawn D. Newsam:
Learning Optical Flow via Dilated Networks and Occlusion Reasoning. ICIP 2018: 3333-3337 - [i18]Yi Zhu, Xueqing Deng, Shawn D. Newsam:
Fine-Grained Land Use Classification at the City Scale Using Ground-Level Images. CoRR abs/1802.02668 (2018) - [i17]Xueqing Deng, Yi Zhu, Shawn D. Newsam:
Spatial Morphing Kernel Regression For Feature Interpolation. CoRR abs/1802.07452 (2018) - [i16]Yi Zhu, Yang Long, Yu Guan, Shawn D. Newsam, Ling Shao:
Towards Universal Representation for Unseen Action Recognition. CoRR abs/1803.08460 (2018) - [i15]Yi Zhu, Shawn D. Newsam:
Learning Optical Flow via Dilated Networks and Occlusion Reasoning. CoRR abs/1805.02733 (2018) - [i14]Xueqing Deng, Yi Zhu, Shawn D. Newsam:
What Is It Like Down There? Generating Dense Ground-Level Views and Image Features From Overhead Imagery Using Conditional Generative Adversarial Networks. CoRR abs/1806.05129 (2018) - [i13]Yi Zhu, Jia Xue, Shawn D. Newsam:
Gated Transfer Network for Transfer Learning. CoRR abs/1810.12521 (2018) - [i12]Yi Zhu, Shawn D. Newsam:
Random Temporal Skipping for Multirate Video Analysis. CoRR abs/1810.12522 (2018) - [i11]Yi Zhu, Karan Sapra, Fitsum A. Reda, Kevin J. Shih, Shawn D. Newsam, Andrew Tao, Bryan Catanzaro:
Improving Semantic Segmentation via Video Propagation and Label Relaxation. CoRR abs/1812.01593 (2018) - 2017
- [c7]Zhen-Zhong Lan, Yi Zhu, Alexander G. Hauptmann, Shawn D. Newsam:
Deep Local Video Feature for Action Recognition. CVPR Workshops 2017: 1219-1225 - [c6]Yi Zhu, Sen Liu, Shawn D. Newsam:
Large-Scale Mapping of Human Activity using Geo-Tagged Videos. SIGSPATIAL/GIS 2017: 68:1-68:4 - [c5]Yi Zhu, Shawn D. Newsam:
DenseNet for dense flow. ICIP 2017: 790-794 - [c4]Yi Zhu, Shawn D. Newsam:
Efficient Action Detection in Untrimmed Videos via Multi-task Learning. WACV 2017: 197-206 - [i10]Zhen-Zhong Lan, Yi Zhu, Alexander G. Hauptmann:
Deep Local Video Feature for Action Recognition. CoRR abs/1701.07368 (2017) - [i9]Yi Zhu, Zhen-Zhong Lan, Shawn D. Newsam, Alexander G. Hauptmann:
Guided Optical Flow Learning. CoRR abs/1702.02295 (2017) - [i8]Yi Zhu, Zhen-Zhong Lan, Shawn D. Newsam, Alexander G. Hauptmann:
Hidden Two-Stream Convolutional Networks for Action Recognition. CoRR abs/1704.00389 (2017) - [i7]Yi Zhu, Shawn D. Newsam, Zaikun Xu:
UC Merced Submission to the ActivityNet Challenge 2016. CoRR abs/1704.03503 (2017) - [i6]Yi Zhu, Sen Liu, Shawn D. Newsam:
Large-Scale Human Activity Mapping using Geo-Tagged Videos. CoRR abs/1706.07911 (2017) - [i5]Yi Zhu, Shawn D. Newsam:
DenseNet for Dense Flow. CoRR abs/1707.06316 (2017) - 2016
- [c3]Yi Zhu, Shawn D. Newsam:
Depth2Action: Exploring Embedded Depth for Large-Scale Action Recognition. ECCV Workshops (1) 2016: 668-684 - [c2]Yi Zhu, Shawn D. Newsam:
Spatio-temporal sentiment hotspot detection using geotagged photos. SIGSPATIAL/GIS 2016: 76:1-76:4 - [i4]Yi Zhu, Shawn D. Newsam:
Depth2Action: Exploring Embedded Depth for Large-Scale Action Recognition. CoRR abs/1608.04339 (2016) - [i3]Yi Zhu, Shawn D. Newsam:
Land Use Classification using Convolutional Neural Networks Applied to Ground-Level Images. CoRR abs/1609.06653 (2016) - [i2]Yi Zhu, Shawn D. Newsam:
Spatio-Temporal Sentiment Hotspot Detection Using Geotagged Photos. CoRR abs/1609.06772 (2016) - [i1]Yi Zhu, Shawn D. Newsam:
Efficient Action Detection in Untrimmed Videos via Multi-Task Learning. CoRR abs/1612.07403 (2016) - 2015
- [c1]Yi Zhu, Shawn D. Newsam:
Land use classification using convolutional neural networks applied to ground-level images. SIGSPATIAL/GIS 2015: 61:1-61:4
Coauthor Index
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