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Haitao Huang

4 papers hereh-index 218 citations9 works total

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

author position
  • first author3
  • last author1

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

fields
  • cs.CV2
  • quant-ph2
same name
  • Haitao Huang — 1 paper
  • Haitao Huang — 1 paper, h 3
  • Haitao Huang — 1 paper, h 82
  • Haitao Huang — 1 paper, h 4
  • Haitao Huang — 1 paper, h 8
  • Haitao Huang — 1 paper, h 2

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 citedQuantum Complex-Valued Self-Attention Model

2 citations · 2 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2026

4DGS-Fixer: Generative Sparse-View 4D Gaussian Splatting with Iterative Refinement Guided by Video Diffusion Priors

Haitao Huang, Shenghao Zhao, Boyuan Tian +7

This paper addresses the challenges of dynamic scene synthesis from sparse-view videos. Existing methods employ geometric priors, adaptive optimization, or density-control strategi…

cs.CV2026

FluSplat: Sparse-View 3D Editing without Test-Time Optimization

Haitao Huang, Shin-Fang Chng, Huangying Zhan +2

Recent advances in text-guided image editing and 3D Gaussian Splatting (3DGS) have enabled high-quality 3D scene manipulation. However, existing pipelines rely on iterative edit-an…

quant-ph2025

Continuous-variable Quantum Diffusion Model for State Generation and Restoration

Haitao Huang, Chuangtao Chen, Qinglin Zhao

The generation and preservation of complex quantum states against environmental noise are paramount challenges in advancing continuous-variable (CV) quantum information processing.…

quant-ph2025★ 2 cited

Quantum Complex-Valued Self-Attention Model

Fu Chen, Qinglin Zhao, Li Feng +3

Self-attention has revolutionized classical machine learning, yet existing quantum self-attention models underutilize quantum states' potential due to oversimplified or incomplete…

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