Bruno Lecouat

According to our database, Bruno Lecouat authored at least 19 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Image Reconstruction from Multiple Shots with Trainable Algorithms. (Reconstruction d'images à partir de prises de vue multiples avec des algorithmes entraînables).

Bruno Lecouat

PhD thesis, 2023

Fine Dense Alignment of Image Bursts through Camera Pose and Depth Estimation.

Bruno Lecouat, Yann Dubois de Mont-Marin, Théo Bodrito, Julien Mairal, Jean Ponce

CoRR, 2023

2022

High dynamic range and super-resolution from raw image bursts.

Bruno Lecouat, Thomas Eboli, Jean Ponce, Julien Mairal

ACM Trans. Graph., 2022

Mixed Membership Generative Adversarial Networks.

Yasin Yazici, Bruno Lecouat, Kim-Hui Yap, Stefan Winkler, Georgios Piliouras, Vijay Chandrasekhar, Chuan-Sheng Foo

Proceedings of the 2022 IEEE International Conference on Image Processing, 2022

2021

NTIRE 2021 Challenge on Burst Super-Resolution: Methods and Results.

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

CoRR, 2021

Aliasing is your Ally: End-to-End Super-Resolution from Raw Image Bursts.

Bruno Lecouat, Jean Ponce, Julien Mairal

CoRR, 2021

Lucas-Kanade Reloaded: End-to-End Super-Resolution from Raw Image Bursts.

Bruno Lecouat, Jean Ponce, Julien Mairal

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020

Designing and Learning Trainable Priors with Non-Cooperative Games.

Bruno Lecouat, Jean Ponce, Julien Mairal

CoRR, 2020

A Flexible Framework for Designing Trainable Priors with Adaptive Smoothing and Game Encoding.

Bruno Lecouat, Jean Ponce, Julien Mairal

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Fully Trainable and Interpretable Non-local Sparse Models for Image Restoration.

Bruno Lecouat, Jean Ponce, Julien Mairal

Proceedings of the Computer Vision - ECCV 2020, 2020

2019

Revisiting Non Local Sparse Models for Image Restoration.

Bruno Lecouat, Jean Ponce, Julien Mairal

CoRR, 2019

Venn GAN: Discovering Commonalities and Particularities of Multiple Distributions.

Yasin Yazici, Bruno Lecouat, Chuan-Sheng Foo, Stefan Winkler, Kim-Hui Yap, Georgios Piliouras, Vijay Chandrasekhar

CoRR, 2019

Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile.

Panayotis Mertikopoulos, Bruno Lecouat, Houssam Zenati, Chuan-Sheng Foo, Vijay Chandrasekhar, Georgios Piliouras

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Semi-Supervised Deep Learning for Abnormality Classification in Retinal Images.

Bruno Lecouat, Ken Chang, Chuan-Sheng Foo, Balagopal Unnikrishnan, James M. Brown, Houssam Zenati, Andrew Beers, Vijay Chandrasekhar, Jayashree Kalpathy-Cramer, Pavitra Krishnaswamy

CoRR, 2018

Manifold regularization with GANs for semi-supervised learning.

Bruno Lecouat, Chuan Sheng Foo, Houssam Zenati, Vijay Chandrasekhar

CoRR, 2018

Mirror descent in saddle-point problems: Going the extra (gradient) mile.

Panayotis Mertikopoulos, Houssam Zenati, Bruno Lecouat, Chuan-Sheng Foo, Vijay Chandrasekhar, Georgios Piliouras

CoRR, 2018

Efficient GAN-Based Anomaly Detection.

Houssam Zenati, Chuan Sheng Foo, Bruno Lecouat, Gaurav Manek, Vijay Ramaseshan Chandrasekhar

CoRR, 2018

Semi-Supervised Learning With GANs: Revisiting Manifold Regularization.

Bruno Lecouat, Chuan Sheng Foo, Houssam Zenati, Vijay Ramaseshan Chandrasekhar

Proceedings of the 6th International Conference on Learning Representations, 2018

Adversarially Learned Anomaly Detection.

Houssam Zenati, Manon Romain, Chuan-Sheng Foo, Bruno Lecouat, Vijay Chandrasekhar

Proceedings of the IEEE International Conference on Data Mining, 2018