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08/22/2023
Time Does Tell: Self-Supervised Time-Tuning of Dense Image Representations
Spatially dense self-supervised learning is a rapidly growing problem do...
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07/08/2023
Learning Variational Neighbor Labels for Test-Time Domain Generalization
This paper strives for domain generalization, where models are trained e...
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06/22/2023
Learning Unseen Modality Interaction
Multimodal learning assumes all modality combinations of interest are av...
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06/16/2023
Multi-Label Meta Weighting for Long-Tailed Dynamic Scene Graph Generation
This paper investigates the problem of scene graph generation in videos ...
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06/08/2023
R-MAE: Regions Meet Masked Autoencoders
Vision-specific concepts such as "region" have played a key role in exte...
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06/08/2023
Focus for Free in Density-Based Counting
This work considers supervised learning to count from images and their c...
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05/17/2023
MetaModulation: Learning Variational Feature Hierarchies for Few-Shot Learning with Fewer Tasks
Meta-learning algorithms are able to learn a new task using previously l...
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04/03/2023
Self-Ordering Point Clouds
In this paper we address the task of finding representative subsets of p...
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03/31/2023
SuperDisco: Super-Class Discovery Improves Visual Recognition for the Long-Tail
Modern image classifiers perform well on populated classes, while degrad...
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03/10/2023
Open-Ended Medical Visual Question Answering Through Prefix Tuning of Language Models
Medical Visual Question Answering (VQA) is an important challenge, as it...
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02/22/2023
Energy-Based Test Sample Adaptation for Domain Generalization
In this paper, we propose energy-based sample adaptation at test time fo...
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01/30/2023
Unlocking Slot Attention by Changing Optimal Transport Costs
Slot attention is a powerful method for object-centric modeling in image...
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01/05/2023
Test of Time: Instilling Video-Language Models with a Sense of Time
Modeling and understanding time remains a challenge in contemporary vide...
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12/23/2022
Detecting Objects with Graph Priors and Graph Refinement
The goal of this paper is to detect objects by exploiting their interrel...
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12/05/2022
Day2Dark: Pseudo-Supervised Activity Recognition beyond Silent Daylight
State-of-the-art activity recognizers are effective during the day, but ...
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10/19/2022
Variational Model Perturbation for Source-Free Domain Adaptation
We aim for source-free domain adaptation, where the task is to deploy a ...
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10/12/2022
Self-Guided Diffusion Models
Diffusion models have demonstrated remarkable progress in image generati...
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10/10/2022
Association Graph Learning for Multi-Task Classification with Category Shifts
In this paper, we focus on multi-task classification, where related clas...
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10/05/2022
Variational prompt tuning improves generalization of vision-language models
Prompt tuning provides an efficient mechanism to adapt large vision-lang...
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05/28/2022
Fake It Till You Make It: Near-Distribution Novelty Detection by Score-Based Generative Models
We aim for image-based novelty detection. Despite considerable progress,...
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04/19/2022
Less than Few: Self-Shot Video Instance Segmentation
The goal of this paper is to bypass the need for labelled examples in fe...
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04/12/2022
LifeLonger: A Benchmark for Continual Disease Classification
Deep learning models have shown a great effectiveness in recognition of ...
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03/27/2022
Audio-Adaptive Activity Recognition Across Video Domains
This paper strives for activity recognition under domain shift, for exam...
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03/23/2022
How Do You Do It? Fine-Grained Action Understanding with Pseudo-Adverbs
We aim to understand how actions are performed and identify subtle diffe...
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02/16/2022
Learning to Generalize across Domains on Single Test Samples
We strive to learn a model from a set of source domains that generalizes...
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12/26/2021
Generative Kernel Continual learning
Kernel continual learning by <cit.> has recently emerged as a strong con...
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12/15/2021
Hierarchical Variational Memory for Few-shot Learning Across Domains
Neural memory enables fast adaptation to new tasks with just a few train...
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11/25/2021
BoxeR: Box-Attention for 2D and 3D Transformers
In this paper, we propose a simple attention mechanism, we call Box-Atte...
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11/23/2021
Multiset-Equivariant Set Prediction with Approximate Implicit Differentiation
Most set prediction models in deep learning use set-equivariant operatio...
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10/27/2021
Feature and Label Embedding Spaces Matter in Addressing Image Classifier Bias
This paper strives to address image classifier bias, with a focus on bot...
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10/25/2021
Diagnosing Errors in Video Relation Detectors
Video relation detection forms a new and challenging problem in computer...
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08/18/2021
Social Fabric: Tubelet Compositions for Video Relation Detection
This paper strives to classify and detect the relationship between objec...
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08/08/2021
Skeleton-Contrastive 3D Action Representation Learning
This paper strives for self-supervised learning of a feature space suita...
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08/06/2021
Feature-Supervised Action Modality Transfer
This paper strives for action recognition and detection in video modalit...
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07/12/2021
Kernel Continual Learning
This paper introduces kernel continual learning, a simple but effective ...
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07/02/2021
On Measuring and Controlling the Spectral Bias of the Deep Image Prior
The deep image prior has demonstrated the remarkable ability that untrai...
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06/26/2021
Recurrently Predicting Hypergraphs
This work considers predicting the relational structure of a hypergraph ...
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06/05/2021
Meta-Learning with Variational Semantic Memory for Word Sense Disambiguation
A critical challenge faced by supervised word sense disambiguation (WSD)...
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06/02/2021
Unsharp Mask Guided Filtering
The goal of this paper is guided image filtering, which emphasizes the i...
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05/14/2021
Attentional Prototype Inference for Few-Shot Semantic Segmentation
This paper aims to address few-shot semantic segmentation. While existin...
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05/09/2021
A Bit More Bayesian: Domain-Invariant Learning with Uncertainty
Domain generalization is challenging due to the domain shift and the unc...
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05/08/2021
MetaKernel: Learning Variational Random Features with Limited Labels
Few-shot learning deals with the fundamental and challenging problem of ...
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05/04/2021
Motion-Augmented Self-Training for Video Recognition at Smaller Scale
The goal of this paper is to self-train a 3D convolutional neural networ...
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04/23/2021
Safe Fakes: Evaluating Face Anonymizers for Face Detectors
Since the introduction of the GDPR and CCPA legislation, both public and...
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04/10/2021
Object Priors for Classifying and Localizing Unseen Actions
This work strives for the classification and localization of human actio...
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04/06/2021
Few-Shot Transformation of Common Actions into Time and Space
This paper introduces the task of few-shot common action localization in...
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04/02/2021
LiftPool: Bidirectional ConvNet Pooling
Pooling is a critical operation in convolutional neural networks for inc...
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03/24/2021
Repetitive Activity Counting by Sight and Sound
This paper strives for repetitive activity counting in videos. Different...
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10/20/2020
Learning to Learn Variational Semantic Memory
In this paper, we introduce variational semantic memory into meta-learni...
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10/08/2020
