b'Matthieu Cord'

research

∙ 09/18/2023

Gradpaint: Gradient-Guided Inpainting with Diffusion Models

Denoising Diffusion Probabilistic Models (DDPMs) have recently achieved ...

0 Asya Grechka, et al. ∙

research

∙ 09/04/2023

DiffHPE: Robust, Coherent 3D Human Pose Lifting with Diffusion

We present an innovative approach to 3D Human Pose Estimation (3D-HPE) b...

0 Cédric Rommel, et al. ∙

research

∙ 07/30/2023

Unified Model for Image, Video, Audio and Language Tasks

Large Language Models (LLMs) have made the ambitious quest for generalis...

0 Mustafa Shukor, et al. ∙

research

∙ 07/18/2023

MOCA: Self-supervised Representation Learning by Predicting Masked Online Codebook Assignments

Self-supervised learning can be used for mitigating the greedy needs of ...

0 Spyros Gidaris, et al. ∙

research

∙ 06/23/2023

Zero-shot spatial layout conditioning for text-to-image diffusion models

Large-scale text-to-image diffusion models have significantly improved t...

0 Guillaume Couairon, et al. ∙

research

∙ 06/21/2023

OBELISC: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents

Large multimodal models trained on natural documents, which interleave i...

0 Hugo Laurençon, et al. ∙

research

∙ 06/15/2023

Challenges of Using Real-World Sensory Inputs for Motion Forecasting in Autonomous Driving

Motion forecasting plays a critical role in enabling robots to anticipat...

0 Yihong Xu, et al. ∙

research

∙ 06/14/2023

Improving Selective Visual Question Answering by Learning from Your Peers

Despite advances in Visual Question Answering (VQA), the ability of mode...

0 Corentin Dancette, et al. ∙

research

∙ 06/07/2023

Rewarded soups: towards Pareto-optimal alignment by interpolating weights fine-tuned on diverse rewards

Foundation models are first pre-trained on vast unsupervised datasets an...

0 Alexandre Ramé, et al. ∙

research

∙ 03/20/2023

eP-ALM: Efficient Perceptual Augmentation of Language Models

Large Language Models (LLMs) have so far impressed the world, with unpre...

0 Mustafa Shukor, et al. ∙

research

∙ 01/24/2023

PowerQuant: Automorphism Search for Non-Uniform Quantization

Deep neural networks (DNNs) are nowadays ubiquitous in many domains such...

0 Edouard Yvinec, et al. ∙

research

∙ 12/20/2022

Recycling diverse models for out-of-distribution generalization

Foundation models are redefining how AI systems are built. Practitioners...

0 Alexandre Ramé, et al. ∙

research

∙ 12/09/2022

Co-training 2^L Submodels for Visual Recognition

We introduce submodel co-training, a regularization method related to co...

4 Hugo Touvron, et al. ∙

research

∙ 12/08/2022

Structured Vision-Language Pretraining for Computational Cooking

Vision-Language Pretraining (VLP) and Foundation models have been the go...

0 Mustafa Shukor, et al. ∙

research

∙ 11/25/2022

CoMFormer: Continual Learning in Semantic and Panoptic Segmentation

Continual learning for segmentation has recently seen increasing interes...

0 Fabio Cermelli, et al. ∙

research

∙ 11/22/2022

OCTET: Object-aware Counterfactual Explanations

Nowadays, deep vision models are being widely deployed in safety-critica...

0 Mehdi Zemni, et al. ∙

research

∙ 10/20/2022

DiffEdit: Diffusion-based semantic image editing with mask guidance

Image generation has recently seen tremendous advances, with diffusion m...

0 Guillaume Couairon, et al. ∙

research

∙ 08/29/2022

Efficient Vision-Language Pretraining with Visual Concepts and Hierarchical Alignment

Vision and Language Pretraining has become the prevalent approach for ta...

24 Mustafa Shukor, et al. ∙

research

∙ 07/08/2022

SInGE: Sparsity via Integrated Gradients Estimation of Neuron Relevance

The leap in performance in state-of-the-art computer vision methods is a...

0 Edouard Yvinec, et al. ∙

research

∙ 06/27/2022

LaRa: Latents and Rays for Multi-Camera Bird's-Eye-View Semantic Segmentation

Recent works in autonomous driving have widely adopted the bird's-eye-vi...

0 Florent Bartoccioni, et al. ∙

research

∙ 05/22/2022

Dynamic Query Selection for Fast Visual Perceiver

Transformers have been matching deep convolutional networks for vision a...

0 Corentin Dancette, et al. ∙

research

∙ 05/20/2022

Swapping Semantic Contents for Mixing Images

Deep architecture have proven capable of solving many tasks provided a s...

0 Rémy Sun, et al. ∙

research

∙ 05/20/2022

Towards efficient feature sharing in MIMO architectures

Multi-input multi-output architectures propose to train multiple subnetw...

0 Rémy Sun, et al. ∙

research

∙ 05/19/2022

Diverse Weight Averaging for Out-of-Distribution Generalization

Standard neural networks struggle to generalize under distribution shift...

9 Alexandre Ramé, et al. ∙

research

∙ 04/25/2022

Multi-Head Distillation for Continual Unsupervised Domain Adaptation in Semantic Segmentation

Unsupervised Domain Adaptation (UDA) is a transfer learning task which a...

9 Antoine Saporta, et al. ∙

research

∙ 04/20/2022

Transformer Decoders with MultiModal Regularization for Cross-Modal Food Retrieval

Cross-modal image-recipe retrieval has gained significant attention in r...

7 Mustafa Shukor, et al. ∙

research

∙ 04/14/2022

DeiT III: Revenge of the ViT

A Vision Transformer (ViT) is a simple neural architecture amenable to s...

21 Hugo Touvron, et al. ∙

research

∙ 03/28/2022

REx: Data-Free Residual Quantization Error Expansion

Deep neural networks (DNNs) are nowadays ubiquitous in the computer visi...

0 Edouard Yvinec, et al. ∙

research

∙ 03/28/2022

SPIQ: Data-Free Per-Channel Static Input Quantization

Computationally expensive neural networks are ubiquitous in computer vis...

0 Edouard Yvinec, et al. ∙

research

∙ 03/18/2022

Three things everyone should know about Vision Transformers

After their initial success in natural language processing, transformer ...

21 Hugo Touvron, et al. ∙

research

∙ 03/09/2022

FlexIT: Towards Flexible Semantic Image Translation

Deep generative models, like GANs, have considerably improved the state ...

0 Guillaume Couairon, et al. ∙

research

∙ 12/27/2021

Augmenting Convolutional networks with attention-based aggregation

We show how to augment any convolutional network with an attention-based...

24 Hugo Touvron, et al. ∙

research

∙ 12/06/2021

CSG0: Continual Urban Scene Generation with Zero Forgetting

With the rapid advances in generative adversarial networks (GANs), the v...

0 Himalaya Jain, et al. ∙

research

∙ 12/06/2021

Embedding Arithmetic for Text-driven Image Transformation

Latent text representations exhibit geometric regularities, such as the ...

0 Guillaume Couairon, et al. ∙

research

∙ 11/22/2021

DyTox: Transformers for Continual Learning with DYnamic TOken eXpansion

Deep network architectures struggle to continually learn new tasks witho...

14 Arthur Douillard, et al. ∙

research

∙ 11/17/2021

STEEX: Steering Counterfactual Explanations with Semantics

As deep learning models are increasingly used in safety-critical applica...

3 Paul Jacob, et al. ∙

research

∙ 11/07/2021

Look at the Variance! Efficient Black-box Explanations with Sobol-based Sensitivity Analysis

We describe a novel attribution method which is grounded in Sensitivity ...

9 Thomas Fel, et al. ∙

research

∙ 09/30/2021

RED++ : Data-Free Pruning of Deep Neural Networks via Input Splitting and Output Merging

Pruning Deep Neural Networks (DNNs) is a prominent field of study in the...

0 Edouard Yvinec, et al. ∙

research

∙ 09/16/2021

Raising context awareness in motion forecasting

Learning-based trajectory prediction models have encountered great succe...

0 Hedi Ben-Younes, et al. ∙

research

∙ 09/08/2021

LiDARTouch: Monocular metric depth estimation with a few-beam LiDAR

Vision-based depth estimation is a key feature in autonomous systems, wh...

0 Florent Bartoccioni, et al. ∙

research

∙ 09/07/2021

Fishr: Invariant Gradient Variances for Out-of-distribution Generalization

Learning robust models that generalize well under changes in the data di...

0 Alexandre Ramé, et al. ∙

research

∙ 08/16/2021

Multi-Target Adversarial Frameworks for Domain Adaptation in Semantic Segmentation

In this work, we address the task of unsupervised domain adaptation (UDA...

0 Antoine Saporta, et al. ∙

research

∙ 06/29/2021

Tackling Catastrophic Forgetting and Background Shift in Continual Semantic Segmentation

Deep learning approaches are nowadays ubiquitously used to tackle comput...

25 Arthur Douillard, et al. ∙

research

∙ 06/03/2021

Semantic Palette: Guiding Scene Generation with Class Proportions

Despite the recent progress of generative adversarial networks (GANs) at...

6 Guillaume Le Moing, et al. ∙

research

∙ 05/31/2021

RED : Looking for Redundancies for Data-Free Structured Compression of Deep Neural Networks

Deep Neural Networks (DNNs) are ubiquitous in today's computer vision la...

0 Edouard Yvinec, et al. ∙

research

∙ 05/07/2021

ResMLP: Feedforward networks for image classification with data-efficient training

We present ResMLP, an architecture built entirely upon multi-layer perce...

43 Hugo Touvron, et al. ∙

research

∙ 04/07/2021

Beyond Question-Based Biases: Assessing Multimodal Shortcut Learning in Visual Question Answering

We introduce an evaluation methodology for visual question answering (VQ...

0 Corentin Dancette, et al. ∙

research

∙ 03/31/2021

Going deeper with Image Transformers

Transformers have been recently adapted for large scale image classifica...

0 Hugo Touvron, et al. ∙

research

∙ 03/10/2021

MixMo: Mixing Multiple Inputs for Multiple Outputs via Deep Subnetworks

Recent strategies achieved ensembling "for free" by fitting concurrently...

0 Alexandre Ramé, et al. ∙

research

∙ 01/14/2021

DICE: Diversity in Deep Ensembles via Conditional Redundancy Adversarial Estimation

Deep ensembles perform better than a single network thanks to the divers...

0 Alexandre Ramé, et al. ∙

Matthieu Cord

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