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ORCIDBruno Lecouat
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2020 – today
- 2023
[b1]Bruno Lecouat:
Image Reconstruction from Multiple Shots with Trainable Algorithms. (Reconstruction d'images à partir de prises de vue multiples avec des algorithmes entraînables). INRIA, Rocquencourt, France, 2023- [i13]Bruno Lecouat, Yann Dubois de Mont-Marin, Théo Bodrito, Julien Mairal, Jean Ponce:
Fine Dense Alignment of Image Bursts through Camera Pose and Depth Estimation. CoRR abs/2312.05190 (2023) - 2022
- [j1]Bruno Lecouat, Thomas Eboli, Jean Ponce, Julien Mairal:
High dynamic range and super-resolution from raw image bursts. ACM Trans. Graph. 41(4): 38:1-38:21 (2022) - [c7]Yasin Yazici, Bruno Lecouat, Kim-Hui Yap, Stefan Winkler, Georgios Piliouras, Vijay Chandrasekhar, Chuan-Sheng Foo:
Mixed Membership Generative Adversarial Networks. ICIP 2022: 1026-1030 - [i12]Bruno Lecouat, Thomas Eboli, Jean Ponce, Julien Mairal:
High Dynamic Range and Super-Resolution from Raw Image Bursts. CoRR abs/2207.14671 (2022) - 2021
- [c6]Bruno Lecouat, Jean Ponce, Julien Mairal:
Lucas-Kanade Reloaded: End-to-End Super-Resolution from Raw Image Bursts. ICCV 2021: 2350-2359 - [i11]Bruno Lecouat, Jean Ponce, Julien Mairal:
Aliasing is your Ally: End-to-End Super-Resolution from Raw Image Bursts. CoRR abs/2104.06191 (2021) - [i10]Goutam Bhat, Martin Danelljan, Radu Timofte, Kazutoshi Akita, Wooyeong Cho, Haoqiang Fan, Lanpeng Jia, Daeshik Kim, Bruno Lecouat, Youwei Li
, Shuaicheng Liu, Ziluan Liu, Ziwei Luo, Takahiro Maeda, Julien Mairal, Christian Micheloni, Xuan Mo, Takeru Oba, Pavel Ostyakov, Jean Ponce, Sanghyeok Son, Jian Sun, Norimichi Ukita, Rao Muhammad Umer, Youliang Yan, Lei Yu, Magauiya Zhussip, Xueyi Zou:
NTIRE 2021 Challenge on Burst Super-Resolution: Methods and Results. CoRR abs/2106.03839 (2021) - 2020
- [c5]Bruno Lecouat, Jean Ponce, Julien Mairal:
Fully Trainable and Interpretable Non-local Sparse Models for Image Restoration. ECCV (22) 2020: 238-254 - [c4]Bruno Lecouat, Jean Ponce, Julien Mairal:
A Flexible Framework for Designing Trainable Priors with Adaptive Smoothing and Game Encoding. NeurIPS 2020 - [i9]Bruno Lecouat, Jean Ponce, Julien Mairal:
Designing and Learning Trainable Priors with Non-Cooperative Games. CoRR abs/2006.14859 (2020)
2010 – 2019
- 2019
- [c3]Panayotis Mertikopoulos, Bruno Lecouat, Houssam Zenati, Chuan-Sheng Foo, Vijay Chandrasekhar, Georgios Piliouras:
Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile. ICLR (Poster) 2019 - [i8]Yasin Yazici, Bruno Lecouat, Chuan-Sheng Foo, Stefan Winkler, Kim-Hui Yap, Georgios Piliouras, Vijay Chandrasekhar:
Venn GAN: Discovering Commonalities and Particularities of Multiple Distributions. CoRR abs/1902.03444 (2019) - [i7]Bruno Lecouat, Jean Ponce, Julien Mairal:
Revisiting Non Local Sparse Models for Image Restoration. CoRR abs/1912.02456 (2019) - 2018
- [c2]Houssam Zenati, Manon Romain, Chuan-Sheng Foo, Bruno Lecouat, Vijay Chandrasekhar:
Adversarially Learned Anomaly Detection. ICDM 2018: 727-736 - [c1]Bruno Lecouat, Chuan Sheng Foo, Houssam Zenati, Vijay Ramaseshan Chandrasekhar:
Semi-Supervised Learning With GANs: Revisiting Manifold Regularization. ICLR (Workshop) 2018 - [i6]Houssam Zenati, Chuan Sheng Foo, Bruno Lecouat, Gaurav Manek, Vijay Ramaseshan Chandrasekhar:
Efficient GAN-Based Anomaly Detection. CoRR abs/1802.06222 (2018) - [i5]Bruno Lecouat, Chuan Sheng Foo, Houssam Zenati, Vijay Ramaseshan Chandrasekhar:
Semi-Supervised Learning with GANs: Revisiting Manifold Regularization. CoRR abs/1805.08957 (2018) - [i4]Panayotis Mertikopoulos, Houssam Zenati, Bruno Lecouat, Chuan-Sheng Foo, Vijay Chandrasekhar, Georgios Piliouras:
Mirror descent in saddle-point problems: Going the extra (gradient) mile. CoRR abs/1807.02629 (2018) - [i3]Bruno Lecouat, Chuan Sheng Foo, Houssam Zenati, Vijay Chandrasekhar:
Manifold regularization with GANs for semi-supervised learning. CoRR abs/1807.04307 (2018) - [i2]Houssam Zenati, Manon Romain, Chuan Sheng Foo, Bruno Lecouat, Vijay Ramaseshan Chandrasekhar:
Adversarially Learned Anomaly Detection. CoRR abs/1812.02288 (2018) - [i1]Bruno Lecouat, Ken Chang, Chuan-Sheng Foo, Balagopal Unnikrishnan, James M. Brown, Houssam Zenati, Andrew Beers, Vijay Chandrasekhar, Jayashree Kalpathy-Cramer, Pavitra Krishnaswamy:
Semi-Supervised Deep Learning for Abnormality Classification in Retinal Images. CoRR abs/1812.07832 (2018)
Coauthor Index
aka: Vijay Ramaseshan Chandrasekhar
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