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Junjie Cao

6 papers hereh-index 2158 citations8 works total

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

author position
  • sole author1
  • first author1
  • middle author4

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.AI1
  • cs.SD1
same name
  • Junjie Cao — 24 papers, h 36
  • Junjie Cao — 10 papers
  • Junjie Cao — 4 papers, h 3
  • Junjie Cao — 3 papers, h 8
  • Junjie Cao — 3 papers, h 2
  • Junjie Cao — 2 papers, h 1

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 citedHigh-Fidelity and Long-Duration Human Image Animation with Diffusion Transformer

1 citations · 1 across the 5 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2025★ 1 cited

High-Fidelity and Long-Duration Human Image Animation with Diffusion Transformer

Shen Zheng, Jiaran Cai, Yuansheng Guan +7

Recent progress in diffusion models has significantly advanced the field of human image animation. While existing methods can generate temporally consistent results for short or re…

cs.CV2025

VideoGuard: Protecting Video Content from Unauthorized Editing

Junjie Cao, Kaizhou Li, Xinchun Yu +2

With the rapid development of generative technology, current generative models can generate high-fidelity digital content and edit it in a controlled manner. However, there is a ri…

cs.CV2024

DisPose: Disentangling Pose Guidance for Controllable Human Image Animation

Hongxiang Li, Yaowei Li, Yuhang Yang +4

Controllable human image animation aims to generate videos from reference images using driving videos. Due to the limited control signals provided by sparse guidance (e.g., skeleto…

cs.CV2024

UVCG: Leveraging Temporal Consistency for Universal Video Protection

KaiZhou Li, Jindong Gu, Xinchun Yu +3

The security risks of AI-driven video editing have garnered significant attention. Although recent studies indicate that adding perturbations to images can protect them from malici…

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