68 citations · 277 across the 25 of their papers we have counts for
9 papers · 1 filter
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…
High-Capacity Expert Binary Networks
Adrian Bulat, Brais Martinez, Georgios Tzimiropoulos
Network binarization is a promising hardware-aware direction for creating efficient deep models. Despite its memory and computational advantages, reducing the accuracy gap between…
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…
Towards Practical Lipreading with Distilled and Efficient Models
Pingchuan Ma, Brais Martinez, Stavros Petridis +1
Lipreading has witnessed a lot of progress due to the resurgence of neural networks. Recent works have placed emphasis on aspects such as improving performance by finding the optim…
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…
Training Binary Neural Networks with Real-to-Binary Convolutions
Brais Martinez, Jing Yang, Adrian Bulat +1
This paper shows how to train binary networks to within a few percent points () of the full precision counterpart. We first show how to build a strong baseline, which…
Knowledge distillation via adaptive instance normalization
Jing Yang, Brais Martinez, Adrian Bulat +1
This paper addresses the problem of model compression via knowledge distillation. To this end, we propose a new knowledge distillation method based on transferring feature statisti…
BATS: Binary ArchitecTure Search
Adrian Bulat, Brais Martinez, Georgios Tzimiropoulos
This paper proposes Binary ArchitecTure Search (BATS), a framework that drastically reduces the accuracy gap between binary neural networks and their real-valued counterparts by me…
Lipreading using Temporal Convolutional Networks
Brais Martinez, Pingchuan Ma, Stavros Petridis +1
Lip-reading has attracted a lot of research attention lately thanks to advances in deep learning. The current state-of-the-art model for recognition of isolated words in-the-wild c…