b'Jakob Verbeek'

research

∙ 08/03/2023

Guided Distillation for Semi-Supervised Instance Segmentation

Although instance segmentation methods have improved considerably, the d...

0 Tariq Berrada, et al. ∙

research

∙ 07/17/2023

Multi-Domain Learning with Modulation Adapters

Deep convolutional networks are ubiquitous in computer vision, due to th...

0 Ekaterina Iakovleva, 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

∙ 05/15/2023

Improved baselines for vision-language pre-training

Contrastive learning has emerged as an efficient framework to learn mult...

0 Enrico Fini, et al. ∙

research

∙ 04/26/2023

Controllable Image Generation via Collage Representations

Recent advances in conditional generative image models have enabled impr...

0 Arantxa Casanova, et al. ∙

research

∙ 04/10/2023

Are Visual Recognition Models Robust to Image Compression?

Reducing the data footprint of visual content via image compression is e...

0 João Maria Janeiro, et al. ∙

research

∙ 04/05/2023

Few-shot Semantic Image Synthesis with Class Affinity Transfer

Semantic image synthesis aims to generate photo realistic images given a...

0 Marlène Careil, et al. ∙

research

∙ 03/16/2023

Instance-Conditioned GAN Data Augmentation for Representation Learning

Data augmentation has become a crucial component to train state-of-the-a...

0 Pietro Astolfi, et al. ∙

research

∙ 01/26/2023

Improving Statistical Fidelity for Neural Image Compression with Implicit Local Likelihood Models

Lossy image compression aims to represent images in as few bits as possi...

0 Matthew J. Muckley, et al. ∙

research

∙ 12/14/2022

Image Compression with Product Quantized Masked Image Modeling

Recent neural compression methods have been based on the popular hyperpr...

0 Alaaeldin El-Nouby, 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

∙ 11/25/2022

Unifying conditional and unconditional semantic image synthesis with OCO-GAN

Generative image models have been extensively studied in recent years. I...

0 Marlène Careil, 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

∙ 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

∙ 09/10/2021

Instance-Conditioned GAN

Generative Adversarial Networks (GANs) can generate near photo realistic...

1 Arantxa Casanova, et al. ∙

research

∙ 06/17/2021

XCiT: Cross-Covariance Image Transformers

Following their success in natural language processing, transformers hav...

0 Alaaeldin El-Nouby, 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

∙ 03/23/2021

DualConv: Dual Mesh Convolutional Networks for Shape Correspondence

Convolutional neural networks have been extremely successful for 2D imag...

0 Nitika Verma, et al. ∙

research

∙ 08/27/2020

Meta-Learning with Shared Amortized Variational Inference

We propose a novel amortized variational inference scheme for an empiric...

6 Ekaterina Iakovleva, et al. ∙

research

∙ 07/20/2020

Discrete Point Flow Networks for Efficient Point Cloud Generation

Generative models have proven effective at modeling 3D shapes and their ...

0 Roman Klokov, et al. ∙

research

∙ 05/18/2020

Efficient Wait-k Models for Simultaneous Machine Translation

Simultaneous machine translation consists in starting output generation ...

0 Maha Elbayad, et al. ∙

research

∙ 03/03/2020

Distilled Hierarchical Neural Ensembles with Adaptive Inference Cost

Deep neural networks form the basis of state-of-the-art models across a ...

0 Adria Ruiz, et al. ∙

research

∙ 09/13/2019

Hierarchical Joint Scene Coordinate Classification and Regression for Visual Localization

Visual localization is pivotal to many applications in computer vision a...

8 Xiaotian Li, et al. ∙

research

∙ 08/20/2019

Probabilistic Reconstruction Networks for 3D Shape Inference from a Single Image

We study end-to-end learning strategies for 3D shape inference from imag...

19 Roman Klokov, et al. ∙

research

∙ 08/19/2019

Adaptative Inference Cost With Convolutional Neural Mixture Models

Despite the outstanding performance of convolutional neural networks (CN...

0 Adria Ruiz, et al. ∙

research

∙ 01/24/2019

Learning Disentangled Representations with Reference-Based Variational Autoencoders

Learning disentangled representations from visual data, where different ...

16 Adria Ruiz, et al. ∙

research

∙ 01/04/2019

Coverage and Quality Driven Training of Generative Image Models

Generative modeling of natural images has been extensively studied in re...

0 Konstantin Shmelkov, et al. ∙

research

∙ 08/15/2018

Scene Coordinate Regression with Angle-Based Reprojection Loss for Camera Relocalization

Image-based camera relocalization is an important problem in computer vi...

0 Xiaotian Li, et al. ∙

research

∙ 08/11/2018

Pervasive Attention: 2D Convolutional Neural Networks for Sequence-to-Sequence Prediction

Current state-of-the-art machine translation systems are based on encode...

0 Maha Elbayad, et al. ∙

research

∙ 06/19/2018

Mixed batches and symmetric discriminators for GAN training

Generative adversarial networks (GANs) are pow- erful generative models ...

0 Thomas Lucas, et al. ∙

research

∙ 05/14/2018

Token-level and sequence-level loss smoothing for RNN language models

Despite the effectiveness of recurrent neural network language models, t...

0 Maha Elbayad, et al. ∙

research

∙ 03/30/2018

Predicting Future Instance Segmentations by Forecasting Convolutional Features

Anticipating future events is an important prerequisite towards intellig...

0 Pauline Luc, et al. ∙

research

∙ 11/30/2017

Auxiliary Guided Autoregressive Variational Autoencoders

Generative modeling of high-dimensional data is a key problem in machine...

0 Thomas Lucas, et al. ∙

research

∙ 06/16/2017

Dynamic Filters in Graph Convolutional Networks

Convolutional neural networks (CNNs) have massively impacted visual reco...

0 Nitika Verma, et al. ∙

research

∙ 03/22/2017

Predicting Deeper into the Future of Semantic Segmentation

The ability to predict and therefore to anticipate the future is an impo...

0 Pauline Luc, et al. ∙

research

∙ 12/03/2016

Areas of Attention for Image Captioning

We propose "Areas of Attention", a novel attention-based model for autom...

0 Marco Pedersoli, et al. ∙

research

∙ 11/25/2016

Semantic Segmentation using Adversarial Networks

Adversarial training has been shown to produce state of the art results ...

0 Pauline Luc, et al. ∙

research

∙ 06/08/2016

Convolutional Neural Fabrics

Despite the success of CNNs, selecting the optimal architecture for a gi...

0 Shreyas Saxena, et al. ∙

research

∙ 03/21/2016

Frankenstein: Learning Deep Face Representations using Small Data

Deep convolutional neural networks have recently proven extremely effect...

0 Guosheng Hu, et al. ∙

research

∙ 10/03/2015

Approximate Fisher Kernels of non-iid Image Models for Image Categorization

The bag-of-words (BoW) model treats images as sets of local descriptors ...

0 Ramazan Gokberk Cinbis, et al. ∙

research

∙ 06/08/2015

Circulant temporal encoding for video retrieval and temporal alignment

We address the problem of specific video event retrieval. Given a query ...

0 Matthijs Douze, et al. ∙

research

∙ 04/21/2015

A robust and efficient video representation for action recognition

This paper introduces a state-of-the-art video representation and applie...

0 Heng Wang, et al. ∙

research

∙ 03/03/2015

Weakly Supervised Object Localization with Multi-fold Multiple Instance Learning

Object category localization is a challenging problem in computer vision...

0 Ramazan Gokberk Cinbis, et al. ∙

Jakob Verbeek

Featured Co-authors