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07/12/2023
Patch n' Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution
The ubiquitous and demonstrably suboptimal choice of resizing images to ...
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06/12/2023
Retrieval-Enhanced Contrastive Vision-Text Models
Contrastive image-text models such as CLIP form the building blocks of m...
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04/13/2023
Verbs in Action: Improving verb understanding in video-language models
Understanding verbs is crucial to modelling how people and objects inter...
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12/15/2022
FlexiViT: One Model for All Patch Sizes
Vision Transformers convert images to sequences by slicing them into pat...
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12/05/2022
Location-Aware Self-Supervised Transformers
Pixel-level labels are particularly expensive to acquire. Hence, pretrai...
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10/10/2022
A Memory Transformer Network for Incremental Learning
We study class-incremental learning, a training setup in which new class...
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04/14/2022
Masked Siamese Networks for Label-Efficient Learning
We propose Masked Siamese Networks (MSN), a self-supervised learning fra...
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02/16/2022
Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision
Discriminative self-supervised learning allows training models on any ra...
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12/16/2021
Towards Unsupervised Dense Information Retrieval with Contrastive Learning
Information retrieval is an important component in natural language proc...
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06/17/2021
XCiT: Cross-Covariance Image Transformers
Following their success in natural language processing, transformers hav...
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05/07/2021
ResMLP: Feedforward networks for image classification with data-efficient training
We present ResMLP, an architecture built entirely upon multi-layer perce...
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04/29/2021
Emerging Properties in Self-Supervised Vision Transformers
In this paper, we question if self-supervised learning provides new prop...
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04/28/2021
Semi-Supervised Learning of Visual Features by Non-Parametrically Predicting View Assignments with Support Samples
This paper proposes a novel method of learning by predicting view assign...
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03/02/2021
Self-supervised Pretraining of Visual Features in the Wild
Recently, self-supervised learning methods like MoCo, SimCLR, BYOL and S...
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06/17/2020
Unsupervised Learning of Visual Features by Contrasting Cluster Assignments
Unsupervised image representations have significantly reduced the gap wi...
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01/10/2020
Pruning Convolutional Neural Networks with Self-Supervision
Convolutional neural networks trained without supervision come close to ...
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05/03/2019
Leveraging Large-Scale Uncurated Data for Unsupervised Pre-training of Visual Features
Pre-training general-purpose visual features with convolutional neural n...
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07/15/2018
