57 citations · 62 across the 5 of their papers we have counts for
10 papers
Sylph: A Hypernetwork Framework for Incremental Few-shot Object Detection
Li Yin, Juan M Perez-Rua, Kevin J Liang
We study the challenging incremental few-shot object detection (iFSD) setting. Recently, hypernetwork-based approaches have been studied in the context of continuous and finetune-f…
SAIC_Cambridge-HuPBA-FBK Submission to the EPIC-Kitchens-100 Action Recognition Challenge 2021
Swathikiran Sudhakaran, Adrian Bulat, Juan-Manuel Perez-Rua +5
This report presents the technical details of our submission to the EPIC-Kitchens-100 Action Recognition Challenge 2021. To participate in the challenge we deployed spatio-temporal…
Space-time Mixing Attention for Video Transformer
Adrian Bulat, Juan-Manuel Perez-Rua, Swathikiran Sudhakaran +2
This paper is on video recognition using Transformers. Very recent attempts in this area have demonstrated promising results in terms of recognition accuracy, yet they have been al…
Boundary-sensitive Pre-training for Temporal Localization in Videos
Mengmeng Xu, Juan-Manuel Perez-Rua, Victor Escorcia +5
Many video analysis tasks require temporal localization thus detection of content changes. However, most existing models developed for these tasks are pre-trained on general video…
Egocentric Action Recognition by Video Attention and Temporal Context
Juan-Manuel Perez-Rua, Antoine Toisoul, Brais Martinez +4
We present the submission of Samsung AI Centre Cambridge to the CVPR2020 EPIC-Kitchens Action Recognition Challenge. In this challenge, action recognition is posed as the problem o…
Knowing What, Where and When to Look: Efficient Video Action Modeling with Attention
Juan-Manuel Perez-Rua, Brais Martinez, Xiatian Zhu +3
Attentive video modeling is essential for action recognition in unconstrained videos due to their rich yet redundant information over space and time. However, introducing attention…