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Hao Zhang

4 papers hereh-index 326 citations5 works total

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

author position
  • middle author4

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

fields
  • cs.CV4
same name
  • Hao Zhang — 32 papers, h 19
  • Hao Zhang — 32 papers, h 38
  • Hao Zhang — 26 papers, h 52
  • Hao Zhang — 24 papers, h 12
  • Hao Zhang — 23 papers, h 22
  • Hao Zhang — 22 papers, h 26

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 citedCNS-Edit: 3D Shape Editing via Coupled Neural Shape Optimization

3 citations · 3 across the 4 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2026

CNS-Edit++: Category-Agnostic 3D Editing with Coupled Neural Shape Representation

Jingyu Hu, Weilong Yan, Zhengzhe Liu +4

This paper presents a latent-space 3D shape editing framework built upon a coupled neural shape (CNS) representation and a neural feature volume optimization. This work extends CNS…

cs.CV2024

CRAYM: Neural Field Optimization via Camera RAY Matching

Liqiang Lin, Wenpeng Wu, Chi-Wing Fu +2

We introduce camera ray matching (CRAYM) into the joint optimization of camera poses and neural fields from multi-view images. The optimized field, referred to as a feature volume,…

cs.CV2024

Depth Estimation Based on 3D Gaussian Splatting Siamese Defocus

Jinchang Zhang, Ningning Xu, Hao Zhang +1

Depth estimation is a fundamental task in 3D geometry. While stereo depth estimation can be achieved through triangulation methods, it is not as straightforward for monocular metho…

cs.CV2024★ 3 cited

CNS-Edit: 3D Shape Editing via Coupled Neural Shape Optimization

Jingyu Hu, Ka-Hei Hui, Zhengzhe Liu +2

This paper introduces a new approach based on a coupled representation and a neural volume optimization to implicitly perform 3D shape editing in latent space. This work has three…

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