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Han Huang

4 papers hereh-index 6151 citations9 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
  • Han Huang — 14 papers, h 7
  • Han Huang — 14 papers, h 7
  • Han Huang — 9 papers, h 8
  • Han Huang — 7 papers, h 1
  • Han Huang — 6 papers, h 2
  • Han Huang — 4 papers, h 8

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

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2025

MonoInstance: Enhancing Monocular Priors via Multi-view Instance Alignment for Neural Rendering and Reconstruction

Wenyuan Zhang, Yixiao Yang, Han Huang +4

Monocular depth priors have been widely adopted by neural rendering in multi-view based tasks such as 3D reconstruction and novel view synthesis. However, due to the inconsistent p…

cs.CV2025

FatesGS: Fast and Accurate Sparse-View Surface Reconstruction using Gaussian Splatting with Depth-Feature Consistency

Han Huang, Yulun Wu, Chao Deng +3

Recently, Gaussian Splatting has sparked a new trend in the field of computer vision. Apart from novel view synthesis, it has also been extended to the area of multi-view reconstru…

cs.CV2025

Sparis: Neural Implicit Surface Reconstruction of Indoor Scenes from Sparse Views

Yulun Wu, Han Huang, Wenyuan Zhang +4

In recent years, reconstructing indoor scene geometry from multi-view images has achieved encouraging accomplishments. Current methods incorporate monocular priors into neural impl…

cs.CV2023

NeuSurf: On-Surface Priors for Neural Surface Reconstruction from Sparse Input Views

Han Huang, Yulun Wu, Junsheng Zhou +3

Recently, neural implicit functions have demonstrated remarkable results in the field of multi-view reconstruction. However, most existing methods are tailored for dense views and…

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