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20212024
most citedTemporal Saliency Query Network for Efficient Video Recognition

2 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2024

Long Context Alignment with Short Instructions and Synthesized Positions

Wenhao Wu, Yizhong Wang, Yao Fu +3

Effectively handling instructions with extremely long context remains a challenge for Large Language Models (LLMs), typically necessitating high-quality long data and substantial c…

cs.CV2023

What Can Simple Arithmetic Operations Do for Temporal Modeling?

Wenhao Wu, Yuxin Song, Zhun Sun +3

Temporal modeling plays a crucial role in understanding video content. To tackle this problem, previous studies built complicated temporal relations through time sequence thanks to…

cs.CV20221 cited

NSNet: Non-saliency Suppression Sampler for Efficient Video Recognition

Boyang Xia, Wenhao Wu, Haoran Wang +5

It is challenging for artificial intelligence systems to achieve accurate video recognition under the scenario of low computation costs. Adaptive inference based efficient video re…

cs.CV20222 cited

Temporal Saliency Query Network for Efficient Video Recognition

Boyang Xia, Zhihao Wang, Wenhao Wu +2

Efficient video recognition is a hot-spot research topic with the explosive growth of multimedia data on the Internet and mobile devices. Most existing methods select the salient f…

cs.CV20211 cited

Temporal Action Proposal Generation with Background Constraint

Haosen Yang, Wenhao Wu, Lining Wang +4

Temporal action proposal generation (TAPG) is a challenging task that aims to locate action instances in untrimmed videos with temporal boundaries. To evaluate the confidence of pr…