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Hao Cheng

5 papers hereh-index 488 citations7 works total

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

author position
  • middle author5

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • eess.IV1
same name
  • Hao Cheng — 44 papers, h 27
  • Hao Cheng — 41 papers, h 39
  • Hao Cheng — 22 papers, h 8
  • Hao Cheng — 10 papers, h 8
  • Hao Cheng — 7 papers, h 6
  • Hao Cheng — 6 papers, h 7

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
20212026
most citedVariational Disentanglement for Domain Generalization

12 citations · 12 across the 4 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2026

Image Diffusion Models Are Good 3D Human Motion Generators

Siyuan Yang, Chong Wang, Hao Cheng +4

Text-to-motion generation typically relies on dataset-specific skeletal representations, with models trained separately for benchmarks with different joint layouts. We investigate…

cs.CV2026

Skeleton-to-Image Encoding: Enabling Skeleton Representation Learning via Vision-Pretrained Models

Siyuan Yang, Jun Liu, Hao Cheng +5

Recent advances in large-scale pretrained vision models have demonstrated impressive capabilities across a wide range of downstream tasks, including cross-modal and multi-modal sce…

cs.CV2025

Reconciling Stochastic and Deterministic Strategies for Zero-shot Image Restoration using Diffusion Model in Dual

Chong Wang, Lanqing Guo, Zixuan Fu +4

Plug-and-play (PnP) methods offer an iterative strategy for solving image restoration (IR) problems in a zero-shot manner, using a learned \textit{discriminative denoiser} as the i…

cs.CV2021★ 12 cited

Variational Disentanglement for Domain Generalization

Yufei Wang, Haoliang Li, Hao Cheng +3

Domain generalization aims to learn an invariant model that can generalize well to the unseen target domain. In this paper, we propose to tackle the problem of domain generalizatio…

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