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researcher

Hengshuang Zhao

29 papers hereh-index 173.7k citations32 works total

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

author position
  • middle author11
  • last author15

Across the 26 of 29 papers where every author was matched, so the position is known.

fields
  • cs.CV27
  • cond-mat.str-el1
  • cs.RO1
same name
  • Hengshuang Zhao — 55 papers, h 43
  • Hengshuang Zhao — 36 papers, h 10
  • Hengshuang Zhao — 28 papers, h 9
  • Hengshuang Zhao — 11 papers, h 7
  • Hengshuang Zhao — 10 papers, h 11
  • Hengshuang Zhao — 5 papers, h 4

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
20232026
most citedDepth Anything: Unleashing the Power of Large-Scale Unlabeled Data

23 citations · 83 across the 27 of their papers we have counts for

collaborators
Showing 2025 · cs.CVShow all

4 papers · 2 filters

cs.CV2025

Concerto: Joint 2D-3D Self-Supervised Learning Emerges Spatial Representations

Yujia Zhang, Xiaoyang Wu, Yixing Lao +4

Humans learn abstract concepts through multisensory synergy, and once formed, such representations can often be recalled from a single modality. Inspired by this principle, we intr…

cs.CV2025

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception

Junjie Wang, Keyu Chen, Yulin Li +4

Dense visual perception tasks have been constrained by their reliance on predefined categories, limiting their applicability in real-world scenarios where visual concepts are unbou…

cs.CV2025

LiteReality: Graphics-Ready 3D Scene Reconstruction from RGB-D Scans

Zhening Huang, Xiaoyang Wu, Fangcheng Zhong +3

We propose LiteReality, a novel pipeline that converts RGB-D scans of indoor environments into compact, realistic, and interactive 3D virtual replicas. LiteReality not only reconst…

cs.CV2025

Sonata: Self-Supervised Learning of Reliable Point Representations

Xiaoyang Wu, Daniel DeTone, Duncan Frost +7

In this paper, we question whether we have a reliable self-supervised point cloud model that can be used for diverse 3D tasks via simple linear probing, even with limited data and…

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