44 citations · 53 across the 7 of their papers we have counts for
6 papers · 1 filter
SMAUG: Sparse Masked Autoencoder for Efficient Video-Language Pre-training
Yuanze Lin, Chen Wei, Huiyu Wang +2
Video-language pre-training is crucial for learning powerful multi-modal representation. However, it typically requires a massive amount of computation. In this paper, we develop S…
REVIVE: Regional Visual Representation Matters in Knowledge-Based Visual Question Answering
Yuanze Lin, Yujia Xie, Dongdong Chen +3
This paper revisits visual representation in knowledge-based visual question answering (VQA) and demonstrates that using regional information in a better way can significantly impr…
Pseudo-Q: Generating Pseudo Language Queries for Visual Grounding
Haojun Jiang, Yuanze Lin, Dongchen Han +2
Visual grounding, i.e., localizing objects in images according to natural language queries, is an important topic in visual language understanding. The most effective approaches fo…
AdaFocus V2: End-to-End Training of Spatial Dynamic Networks for Video Recognition
Yulin Wang, Yang Yue, Yuanze Lin +6
Recent works have shown that the computational efficiency of video recognition can be significantly improved by reducing the spatial redundancy. As a representative work, the adapt…
Self-Supervised Video Representation Learning with Meta-Contrastive Network
Yuanze Lin, Xun Guo, Yan Lu
Self-supervised learning has been successfully applied to pre-train video representations, which aims at efficient adaptation from pre-training domain to downstream tasks. Existing…
An Action Recognition network for specific target based on rMC and RPN
Mingjie Li, Youqian Feng, Zhonghai Yin +4
The traditional methods of action recognition are not specific for the operator, thus results are easy to be disturbed when other actions are operated in videos. The network based…