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09/15/2023
Optimization of Rank Losses for Image Retrieval
In image retrieval, standard evaluation metrics rely on score ranking, a...
share
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07/13/2023
Leveraging Vision-Language Foundation Models for Fine-Grained Downstream Tasks
Vision-language foundation models such as CLIP have shown impressive zer...
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06/14/2023
VidEdit: Zero-Shot and Spatially Aware Text-Driven Video Editing
Recently, diffusion-based generative models have achieved remarkable suc...
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05/26/2023
Hybrid Energy Based Model in the Feature Space for Out-of-Distribution Detection
Out-of-distribution (OOD) detection is a critical requirement for the de...
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02/07/2023
Diverse Probabilistic Trajectory Forecasting with Admissibility Constraints
Predicting multiple trajectories for road users is important for automat...
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12/15/2022
Full Contextual Attention for Multi-resolution Transformers in Semantic Segmentation
Transformers have proved to be very effective for visual recognition tas...
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12/08/2022
Structured Vision-Language Pretraining for Computational Cooking
Vision-Language Pretraining (VLP) and Foundation models have been the go...
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10/11/2022
Memory transformers for full context and high-resolution 3D Medical Segmentation
Transformer models achieve state-of-the-art results for image segmentati...
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08/26/2022
Take One Gram of Neural Features, Get Enhanced Group Robustness
Predictive performance of machine learning models trained with empirical...
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07/08/2022
Complementing Brightness Constancy with Deep Networks for Optical Flow Prediction
State-of-the-art methods for optical flow estimation rely on deep learni...
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07/05/2022
Hierarchical Average Precision Training for Pertinent Image Retrieval
Image Retrieval is commonly evaluated with Average Precision (AP) or Rec...
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05/20/2022
Swapping Semantic Contents for Mixing Images
Deep architecture have proven capable of solving many tasks provided a s...
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05/20/2022
Towards efficient feature sharing in MIMO architectures
Multi-input multi-output architectures propose to train multiple subnetw...
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10/01/2021
Robust and Decomposable Average Precision for Image Retrieval
In image retrieval, standard evaluation metrics rely on score ranking, e...
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04/09/2021
Deep Time Series Forecasting with Shape and Temporal Criteria
This paper addresses the problem of multi-step time series forecasting f...
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03/10/2021
U-Net Transformer: Self and Cross Attention for Medical Image Segmentation
Medical image segmentation remains particularly challenging for complex ...
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12/11/2020
Confidence Estimation via Auxiliary Models
Reliably quantifying the confidence of deep neural classifiers is a chal...
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10/14/2020
Probabilistic Time Series Forecasting with Structured Shape and Temporal Diversity
Probabilistic forecasting consists in predicting a distribution of possi...
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10/09/2020
Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting
Forecasting complex dynamical phenomena in settings where only partial k...
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03/03/2020
Disentangling Physical Dynamics from Unknown Factors for Unsupervised Video Prediction
Leveraging physical knowledge described by partial differential equation...
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09/19/2019
Shape and Time Distortion Loss for Training Deep Time Series Forecasting Models
This paper addresses the problem of time series forecasting for non-stat...
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06/03/2019
DualDis: Dual-Branch Disentangling with Adversarial Learning
In computer vision, disentangling techniques aim at improving latent rep...
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02/25/2019
MUREL: Multimodal Relational Reasoning for Visual Question Answering
Multimodal attentional networks are currently state-of-the-art models fo...
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01/31/2019
BLOCK: Bilinear Superdiagonal Fusion for Visual Question Answering and Visual Relationship Detection
Multimodal representation learning is gaining more and more interest wit...
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07/30/2018
HybridNet: Classification and Reconstruction Cooperation for Semi-Supervised Learning
In this paper, we introduce a new model for leveraging unlabeled data to...
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04/30/2018
Cross-Modal Retrieval in the Cooking Context: Learning Semantic Text-Image Embeddings
Designing powerful tools that support cooking activities has rapidly gai...
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04/29/2018
SHARE: Regularization for Deep Learning
Regularization is a big issue for training deep neural networks. In this...
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04/29/2018
SHADE: Information-Based Regularization for Deep Learning
Regularization is a big issue for training deep neural networks. In this...
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07/19/2017
Deformable Part-based Fully Convolutional Network for Object Detection
Existing region-based object detectors are limited to regions with fixed...
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05/18/2017
MUTAN: Multimodal Tucker Fusion for Visual Question Answering
Bilinear models provide an appealing framework for mixing and merging in...
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11/29/2016
Gossip training for deep learning
We address the issue of speeding up the training of convolutional networ...
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10/25/2016
Maxmin convolutional neural networks for image classification
Convolutional neural networks (CNN) are widely used in computer vision, ...
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10/18/2016
Master's Thesis : Deep Learning for Visual Recognition
The goal of our research is to develop methods advancing automatic visua...
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10/18/2016
M2CAI Workflow Challenge: Convolutional Neural Networks with Time Smoothing and Hidden Markov Model for Video Frames Classification
Our approach is among the three best to tackle the M2CAI Workflow challe...
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12/20/2013
