b'Jean Ponce'

research

∙ 08/03/2023

Revisiting Deformable Convolution for Depth Completion

Depth completion, which aims to generate high-quality dense depth maps f...

0 Xinglong Sun, et al. ∙

research

∙ 07/24/2023

MC-JEPA: A Joint-Embedding Predictive Architecture for Self-Supervised Learning of Motion and Content Features

Self-supervised learning of visual representations has been focusing on ...

0 Adrien Bardes, et al. ∙

research

∙ 06/21/2023

Combining multi-spectral data with statistical and deep-learning models for improved exoplanet detection in direct imaging at high contrast

Exoplanet detection by direct imaging is a difficult task: the faint sig...

0 Olivier Flasseur, et al. ∙

research

∙ 04/12/2023

An Image Quality Assessment Dataset for Portraits

Year after year, the demand for ever-better smartphone photos continues ...

0 Nicolas Chahine, et al. ∙

research

∙ 03/22/2023

Pixel-wise Agricultural Image Time Series Classification: Comparisons and a Deformable Prototype-based Approach

Improvements in Earth observation by satellites allow for imagery of eve...

0 Elliot Vincent, et al. ∙

research

∙ 11/25/2022

WALDO: Future Video Synthesis using Object Layer Decomposition and Parametric Flow Prediction

This paper presents WALDO (WArping Layer-Decomposed Objects), a novel ap...

0 Guillaume Le Moing, et al. ∙

research

∙ 11/21/2022

A minimum swept-volume metric structure for configuration space

Borrowing elementary ideas from solid mechanics and differential geometr...

0 Yann de Mont-Marin, et al. ∙

research

∙ 11/16/2022

Learning Reward Functions for Robotic Manipulation by Observing Humans

Observing a human demonstrator manipulate objects provides a rich, scala...

1 Minttu Alakuijala, et al. ∙

research

∙ 10/04/2022

VICRegL: Self-Supervised Learning of Local Visual Features

Most recent self-supervised methods for learning image representations f...

12 Adrien Bardes, et al. ∙

research

∙ 07/29/2022

High Dynamic Range and Super-Resolution from Raw Image Bursts

Photographs captured by smartphones and mid-range cameras have limited s...

0 Bruno Lecouat, et al. ∙

research

∙ 07/25/2022

Active Learning Strategies for Weakly-supervised Object Detection

Object detectors trained with weak annotations are affordable alternativ...

0 Huy V. Vo, et al. ∙

research

∙ 04/20/2022

Assembly Planning from Observations under Physical Constraints

This paper addresses the problem of copying an unknown assembly of primi...

4 Thomas Chabal, et al. ∙

research

∙ 09/29/2021

Localizing Objects with Self-Supervised Transformers and no Labels

Localizing objects in image collections without supervision can help to ...

5 Oriane Siméoni, et al. ∙

research

∙ 07/16/2021

CCVS: Context-aware Controllable Video Synthesis

This presentation introduces a self-supervised learning approach to the ...

5 Guillaume Le Moing, et al. ∙

research

∙ 06/15/2021

Residual Reinforcement Learning from Demonstrations

Residual reinforcement learning (RL) has been proposed as a way to solve...

6 Minttu Alakuijala, et al. ∙

research

∙ 06/12/2021

Large-Scale Unsupervised Object Discovery

Existing approaches to unsupervised object discovery (UOD) do not scale ...

38 Huy V. Vo, et al. ∙

research

∙ 06/07/2021

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

This paper reviews the NTIRE2021 challenge on burst super-resolution. Gi...

0 Goutam Bhat, et al. ∙

research

∙ 05/11/2021

VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning

Recent self-supervised methods for image representation learning are bas...

23 Adrien Bardes, et al. ∙

research

∙ 04/29/2021

Unsupervised Layered Image Decomposition into Object Prototypes

We present an unsupervised learning framework for decomposing images int...

18 Tom Monnier, et al. ∙

research

∙ 04/13/2021

Learning to Jointly Deblur, Demosaick and Denoise Raw Images

We address the problem of non-blind deblurring and demosaicking of noisy...

0 Thomas Eboli, et al. ∙

research

∙ 04/13/2021

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

This presentation addresses the problem of reconstructing a high-resolut...

0 Bruno Lecouat, et al. ∙

research

∙ 07/21/2020

Learning to Compose Hypercolumns for Visual Correspondence

Feature representation plays a crucial role in visual correspondence, an...

1 Juhong Min, et al. ∙

research

∙ 07/06/2020

Toward unsupervised, multi-object discovery in large-scale image collections

This paper addresses the problem of discovering the objects present in a...

0 Huy V. Vo, et al. ∙

research

∙ 07/03/2020

End-to-end Interpretable Learning of Non-blind Image Deblurring

Non-blind image deblurring is typically formulated as a linear least-squ...

0 Thomas Eboli, et al. ∙

research

∙ 06/26/2020

Designing and Learning Trainable Priors with Non-Cooperative Games

We introduce a general framework for designing and learning neural netwo...

11 Bruno Lecouat, et al. ∙

research

∙ 06/16/2020

Structured and Localized Image Restoration

We present a novel approach to image restoration that leverages ideas fr...

10 Thomas Eboli, et al. ∙

research

∙ 12/05/2019

Revisiting Non Local Sparse Models for Image Restoration

We propose a differentiable algorithm for image restoration inspired by ...

4 Bruno Lecouat, et al. ∙

research

∙ 11/29/2019

Learning Semantic Correspondence Exploiting an Object-level Prior

We address the problem of semantic correspondence, that is, establishing...

2 Junghyup Lee, et al. ∙

research

∙ 10/17/2019

Deformable Kernel Networks for Joint Image Filtering

Joint image filters are used to transfer structural details from a guida...

12 Beomjun Kim, et al. ∙

research

∙ 08/28/2019

SPair-71k: A Large-scale Benchmark for Semantic Correspondence

Establishing visual correspondences under large intra-class variations, ...

1 Juhong Min, et al. ∙

research

∙ 08/18/2019

Hyperpixel Flow: Semantic Correspondence with Multi-layer Neural Features

Establishing visual correspondences under large intra-class variations r...

2 Juhong Min, et al. ∙

research

∙ 04/05/2019

Unsupervised Image Matching and Object Discovery as Optimization

Learning with complete or partial supervision is powerful but relies on ...

40 Huy V. Vo, et al. ∙

research

∙ 04/03/2019

SFNet: Learning Object-aware Semantic Correspondence

We address the problem of semantic correspondence, that is, establishing...

0 Junghyup Lee, et al. ∙

research

∙ 03/27/2019

Deformable kernel networks for guided depth map upsampling

We address the problem of upsampling a low-resolution (LR) depth map usi...

0 Beomjun Kim, et al. ∙

research

∙ 08/08/2018

On the Solvability of Viewing Graphs

A set of fundamental matrices relating pairs of cameras in some configur...

0 Matthew Trager, et al. ∙

research

∙ 05/11/2017

SCNet: Learning Semantic Correspondence

This paper addresses the problem of establishing semantic correspondence...

0 Kai Han, et al. ∙

research

∙ 03/21/2017

Proposal Flow: Semantic Correspondences from Object Proposals

Finding image correspondences remains a challenging problem in the prese...

0 Bumsub Ham, et al. ∙

research

∙ 12/04/2016

General models for rational cameras and the case of two-slit projections

The rational camera model recently introduced in [19] provides a general...

0 Matthew Trager, et al. ∙

research

∙ 08/21/2016

Congruences and Concurrent Lines in Multi-View Geometry

We present a new framework for multi-view geometry in computer vision. A...

0 Jean Ponce, et al. ∙

research

∙ 03/02/2015

Learning a Convolutional Neural Network for Non-uniform Motion Blur Removal

In this paper, we address the problem of estimating and removing non-uni...

0 Jian Sun, et al. ∙

research

∙ 01/25/2015

Unsupervised Object Discovery and Localization in the Wild: Part-based Matching with Bottom-up Region Proposals

This paper addresses unsupervised discovery and localization of dominant...

0 Minsu Cho, et al. ∙

research

∙ 11/12/2014

Sparse Modeling for Image and Vision Processing

In recent years, a large amount of multi-disciplinary research has been ...

0 Julien Mairal, et al. ∙

research

∙ 07/04/2014

Weakly Supervised Action Labeling in Videos Under Ordering Constraints

We are given a set of video clips, each one annotated with an ordered l...

0 Piotr Bojanowski, et al. ∙

research

∙ 10/13/2011

Sparse Image Representation with Epitomes

Sparse coding, which is the decomposition of a vector using only a few b...

0 Louise Benoît, et al. ∙

research

∙ 10/05/2011

Dictionary Learning for Deblurring and Digital Zoom

This paper proposes a novel approach to image deblurring and digital zoo...

0 Florent Couzinie-Devy, et al. ∙

research

∙ 09/27/2010

Task-Driven Dictionary Learning

Modeling data with linear combinations of a few elements from a learned ...

0 Julien Mairal, et al. ∙

research

∙ 09/18/2008

Supervised Dictionary Learning

It is now well established that sparse signal models are well suited to ...

0 Julien Mairal, et al. ∙

Jean Ponce

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