234 citations · 636 across the 14 of their papers we have counts for
5 papers · 2 filters
Self-Supervised Learning for Endoscopic Video Analysis
Roy Hirsch, Mathilde Caron, Regev Cohen +6
Self-supervised learning (SSL) has led to important breakthroughs in computer vision by allowing learning from large amounts of unlabeled data. As such, it might have a pivotal rol…
Patch n' Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution
Mostafa Dehghani, Basil Mustafa, Josip Djolonga +12
The ubiquitous and demonstrably suboptimal choice of resizing images to a fixed resolution before processing them with computer vision models has not yet been successfully challeng…
Retrieval-Enhanced Contrastive Vision-Text Models
Ahmet Iscen, Mathilde Caron, Alireza Fathi +1
Contrastive image-text models such as CLIP form the building blocks of many state-of-the-art systems. While they excel at recognizing common generic concepts, they still struggle o…
Verbs in Action: Improving verb understanding in video-language models
Liliane Momeni, Mathilde Caron, Arsha Nagrani +2
Understanding verbs is crucial to modelling how people and objects interact with each other and the environment through space and time. Recently, state-of-the-art video-language mo…
Scaling Vision Transformers to 22 Billion Parameters
Mostafa Dehghani, Josip Djolonga, Basil Mustafa +39
The scaling of Transformers has driven breakthrough capabilities for language models. At present, the largest large language models (LLMs) contain upwards of 100B parameters. Visio…