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Wenbin Wang

4 papers hereh-index 7433 citations11 works total

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

author position
  • first author2
  • middle author2

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV4
same name
  • Wenbin Wang — 16 papers, h 18
  • Wenbin Wang — 7 papers, h 5
  • Wenbin Wang — 5 papers, h 3
  • Wenbin Wang — 5 papers, h 2
  • Wenbin Wang — 3 papers, h 2
  • Wenbin Wang — 3 papers, h 2

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
20202022
most citedSketching Image Gist: Human-Mimetic Hierarchical Scene Graph Generation

10 citations · 18 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2022★ 4 cited

MAFW: A Large-scale, Multi-modal, Compound Affective Database for Dynamic Facial Expression Recognition in the Wild

Yuanyuan Liu, Wei Dai, Chuanxu Feng +4

Dynamic facial expression recognition (FER) databases provide important data support for affective computing and applications. However, most FER databases are annotated with severa…

cs.CV2021

Topic Scene Graph Generation by Attention Distillation from Caption

W. Wang, R. Wang, X. Chen

If an image tells a story, the image caption is the briefest narrator. Generally, a scene graph prefers to be an omniscient generalist, while the image caption is more willing to b…

cs.CV2021★ 4 cited

Expression Snippet Transformer for Robust Video-based Facial Expression Recognition

Yuanyuan Liu, Wenbin Wang, Chuanxu Feng +3

The recent success of Transformer has provided a new direction to various visual understanding tasks, including video-based facial expression recognition (FER). By modeling visual…

cs.CV2020★ 10 cited

Sketching Image Gist: Human-Mimetic Hierarchical Scene Graph Generation

Wenbin Wang, Ruiping Wang, Shiguang Shan +1

Scene graph aims to faithfully reveal humans' perception of image content. When humans analyze a scene, they usually prefer to describe image gist first, namely major objects and k…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.