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Yunsheng Wu

6 papers hereh-index 11729 citations13 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author4
  • last author2

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.CL1
  • cs.IR1
same name
  • Yunsheng Wu — 15 papers, h 10
  • Yunsheng Wu — 7 papers, h 4
  • Yunsheng Wu — 6 papers, h 4
  • Yunsheng Wu — 2 papers

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20182024
most citedFacial Action Unit Detection Using Attention and Relation Learning

96 citations · 142 across the 6 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2024★ 5 cited

VITA: Towards Open-Source Interactive Omni Multimodal LLM

Chaoyou Fu, Haojia Lin, Zuwei Long +16

The remarkable multimodal capabilities and interactive experience of GPT-4o underscore their necessity in practical applications, yet open-source models rarely excel in both areas.…

cs.CV2023★ 2 cited

Aligning and Prompting Everything All at Once for Universal Visual Perception

Yunhang Shen, Chaoyou Fu, Peixian Chen +6

Vision foundation models have been explored recently to build general-purpose vision systems. However, predominant paradigms, driven by casting instance-level tasks as an object-wo…

cs.CV2019★ 29 cited

DDPNAS: Efficient Neural Architecture Search via Dynamic Distribution Pruning

Xiawu Zheng, Chenyi Yang, Shaokun Zhang +6

Neural Architecture Search (NAS) has demonstrated state-of-the-art performance on various computer vision tasks. Despite the superior performance achieved, the efficiency and gener…

cs.CV2018★ 96 cited

Facial Action Unit Detection Using Attention and Relation Learning

Zhiwen Shao, Zhilei Liu, Jianfei Cai +2

Attention mechanism has recently attracted increasing attentions in the field of facial action unit (AU) detection. By finding the region of interest of each AU with the attention…

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