24 citations · 97 across the 24 of their papers we have counts for
5 papers · 1 filter
Semi-supervised Vision Transformers at Scale
Zhaowei Cai, Avinash Ravichandran, Paolo Favaro +5
We study semi-supervised learning (SSL) for vision transformers (ViT), an under-explored topic despite the wide adoption of the ViT architectures to different tasks. To tackle this…
What to look at and where: Semantic and Spatial Refined Transformer for detecting human-object interactions
A S M Iftekhar, Hao Chen, Kaustav Kundu +3
We propose a novel one-stage Transformer-based semantic and spatial refined transformer (SSRT) to solve the Human-Object Interaction detection task, which requires to localize huma…
SCVRL: Shuffled Contrastive Video Representation Learning
Michael Dorkenwald, Fanyi Xiao, Biagio Brattoli +2
We propose SCVRL, a novel contrastive-based framework for self-supervised learning for videos. Differently from previous contrast learning based methods that mostly focus on learni…
Hierarchical Self-supervised Representation Learning for Movie Understanding
Fanyi Xiao, Kaustav Kundu, Joseph Tighe +1
Most self-supervised video representation learning approaches focus on action recognition. In contrast, in this paper we focus on self-supervised video learning for movie understan…
Transfer of Representations to Video Label Propagation: Implementation Factors Matter
Daniel McKee, Zitong Zhan, Bing Shuai +3
This work studies feature representations for dense label propagation in video, with a focus on recently proposed methods that learn video correspondence using self-supervised sign…