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Chenliang Xu

61 papers hereh-index 397k citations105 works total

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

author position
  • first author5
  • middle author17
  • last author38

Across the 60 of 61 papers where every author was matched, so the position is known.

fields
  • cs.CV49
  • cs.LG5
  • eess.IV2
  • cs.HC1
  • cs.RO1
  • cs.SD1
same name
  • Chenliang Xu — 18 papers, h 11
  • Chenliang Xu — 18 papers, h 9
  • Chenliang Xu — 14 papers, h 6
  • Chenliang Xu — 13 papers, h 9
  • Chenliang Xu — 8 papers
  • Chenliang Xu — 7 papers, h 5

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
20132023
most citedTowards Automatic Learning of Procedures from Web Instructional Videos

216 citations · 802 across the 61 of their papers we have counts for

collaborators
Showing 2017Show all

4 papers · 1 filter

cs.CV2017★ 55 cited

TricorNet: A Hybrid Temporal Convolutional and Recurrent Network for Video Action Segmentation

Li Ding, Chenliang Xu

Action segmentation as a milestone towards building automatic systems to understand untrimmed videos has received considerable attention in the recent years. It is typically being…

cs.CV2017★ 1 cited

Action Understanding with Multiple Classes of Actors

Chenliang Xu, Caiming Xiong, Jason J. Corso

Despite the rapid progress, existing works on action understanding focus strictly on one type of action agent, which we call actor---a human adult, ignoring the diversity of action…

cs.CV2017★ 7 cited

Deep Cross-Modal Audio-Visual Generation

Lele Chen, Sudhanshu Srivastava, Zhiyao Duan +1

Cross-modal audio-visual perception has been a long-lasting topic in psychology and neurology, and various studies have discovered strong correlations in human perception of audito…

cs.CV2017★ 216 cited

Towards Automatic Learning of Procedures from Web Instructional Videos

Luowei Zhou, Chenliang Xu, Jason J. Corso

The potential for agents, whether embodied or software, to learn by observing other agents performing procedures involving objects and actions is rich. Current research on automati…

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