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08/18/2023
On the Effectiveness of LayerNorm Tuning for Continual Learning in Vision Transformers
State-of-the-art rehearsal-free continual learning methods exploit the p...
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08/03/2023
Guided Distillation for Semi-Supervised Instance Segmentation
Although instance segmentation methods have improved considerably, the d...
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07/17/2023
Multi-Domain Learning with Modulation Adapters
Deep convolutional networks are ubiquitous in computer vision, due to th...
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06/13/2023
Semi-supervised learning made simple with self-supervised clustering
Self-supervised learning models have been shown to learn rich visual rep...
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04/18/2023
Think Before You Act: Unified Policy for Interleaving Language Reasoning with Actions
The success of transformer models trained with a language modeling objec...
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01/05/2023
Learning Goal-Conditioned Policies Offline with Self-Supervised Reward Shaping
Developing agents that can execute multiple skills by learning from pre-...
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12/16/2022
Fake it till you make it: Learning(s) from a synthetic ImageNet clone
Recent large-scale image generation models such as Stable Diffusion have...
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12/09/2022
A soft nearest-neighbor framework for continual semi-supervised learning
Despite significant advances, the performance of state-of-the-art contin...
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12/01/2022
From CNNs to Shift-Invariant Twin Wavelet Models
We propose a novel antialiasing method to increase shift invariance in c...
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11/29/2022
Lightweight Structure-Aware Attention for Visual Understanding
Vision Transformers (ViTs) have become a dominant paradigm for visual re...
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10/21/2022
Self-Supervised Pretraining on Satellite Imagery: a Case Study on Label-Efficient Vehicle Detection
In defense-related remote sensing applications, such as vehicle detectio...
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10/13/2022
Evaluating the Label Efficiency of Contrastive Self-Supervised Learning for Multi-Resolution Satellite Imagery
The application of deep neural networks to remote sensing imagery is oft...
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09/19/2022
On the Shift Invariance of Max Pooling Feature Maps in Convolutional Neural Networks
In this paper, we aim to improve the mathematical interpretability of co...
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06/30/2022
Improving the Generalization of Supervised Models
We consider the problem of training a deep neural network on a given cla...
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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...
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06/23/2022
Walk the Random Walk: Learning to Discover and Reach Goals Without Supervision
Learning a diverse set of skills by interacting with an environment with...
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06/15/2022
AVATAR: Unconstrained Audiovisual Speech Recognition
Audio-visual automatic speech recognition (AV-ASR) is an extension of AS...
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02/28/2022
The Right Spin: Learning Object Motion from Rotation-Compensated Flow Fields
Both a good understanding of geometrical concepts and a broad familiarit...
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12/08/2021
Self-Supervised Models are Continual Learners
Self-supervised models have been shown to produce comparable or better v...
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11/01/2021
Masking Modalities for Cross-modal Video Retrieval
Pre-training on large scale unlabelled datasets has shown impressive per...
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10/27/2021
Regularized Frank-Wolfe for Dense CRFs: Generalizing Mean Field and Beyond
We introduce regularized Frank-Wolfe, a general and effective algorithm ...
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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...
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01/13/2021
Memory-Augmented Reinforcement Learning for Image-Goal Navigation
In this work, we address the problem of image-goal navigation in the con...
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12/10/2020
Concept Generalization in Visual Representation Learning
Measuring concept generalization, i.e., the extent to which models train...
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08/27/2020
Meta-Learning with Shared Amortized Variational Inference
We propose a novel amortized variational inference scheme for an empiric...
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07/21/2020
Multi-modal Transformer for Video Retrieval
The task of retrieving video content relevant to natural language querie...
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01/04/2019
Coverage and Quality Driven Training of Generative Image Models
Generative modeling of natural images has been extensively studied in re...
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07/25/2018
End-to-End Incremental Learning
Although deep learning approaches have stood out in recent years due to ...
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07/25/2018
How good is my GAN?
Generative adversarial networks (GANs) are one of the most popular metho...
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04/25/2018
Actor and Observer: Joint Modeling of First and Third-Person Videos
Several theories in cognitive neuroscience suggest that when people inte...
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04/25/2018
Charades-Ego: A Large-Scale Dataset of Paired Third and First Person Videos
In Actor and Observer we introduced a dataset linking the first and thir...
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12/01/2017
Learning to Segment Moving Objects
We study the problem of segmenting moving objects in unconstrained video...
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08/23/2017
Incremental Learning of Object Detectors without Catastrophic Forgetting
Despite their success for object detection, convolutional neural network...
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07/19/2017
Detecting Parts for Action Localization
In this paper, we propose a new framework for action localization that t...
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12/21/2016
Learning Motion Patterns in Videos
The problem of determining whether an object is in motion, irrespective ...
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03/23/2016
Weakly-Supervised Semantic Segmentation using Motion Cues
Fully convolutional neural networks (FCNNs) trained on a large number of...
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01/13/2016
Enhancing Energy Minimization Framework for Scene Text Recognition with Top-Down Cues
Recognizing scene text is a challenging problem, even more so than the r...
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08/29/2011