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researcher

Ying Wu

4 papers here

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

author position
  • middle author2
  • last author2

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

fields
  • cs.RO2
  • cs.CV1
  • cs.LG1
ORCID 0000-0001-8029-3664
same name
  • Ying Wu — 15 papers, h 53
  • Ying Wu — 7 papers, h 65
  • Ying Wu — 5 papers, h 31
  • Ying Wu — 5 papers
  • Ying Wu — 3 papers
  • Ying Wu — 1 paper

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

most citedHALMA: Humanlike Abstraction Learning Meets Affordance in Rapid Problem Solving

8 citations · 16 across the 4 of their papers we have counts for

collaborators

4 papers

cs.RO2021★ 5 cited

Congestion-aware Multi-agent Trajectory Prediction for Collision Avoidance

Xu Xie, Chi Zhang, Yixin Zhu +2

Predicting agents' future trajectories plays a crucial role in modern AI systems, yet it is challenging due to intricate interactions exhibited in multi-agent systems, especially w…

cs.RO2021★ 2 cited

MetaView: Few-shot Active Object Recognition

Wei Wei, Haonan Yu, Haichao Zhang +2

In robot sensing scenarios, instead of passively utilizing human captured views, an agent should be able to actively choose informative viewpoints of a 3D object as discriminative…

cs.LG2021★ 8 cited

HALMA: Humanlike Abstraction Learning Meets Affordance in Rapid Problem Solving

Sirui Xie, Xiaojian Ma, Peiyu Yu +3

Humans learn compositional and causal abstraction, \ie, knowledge, in response to the structure of naturalistic tasks. When presented with a problem-solving task involving some obj…

cs.CV2014★ 1 cited

Scalable Matting: A Sub-linear Approach

Philip G. Lee, Ying Wu

Natural image matting, which separates foreground from background, is a very important intermediate step in recent computer vision algorithms. However, it is severely underconstrai…

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