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Gang Cao

4 papers here

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

author position
  • middle author3
  • last author1

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

fields
  • cs.CV4
ORCID 0000-0002-4549-0125
same name
  • Gang Cao — 19 papers
  • Gang Cao — 7 papers, h 17
  • Gang Cao — 5 papers
  • Gang Cao — 4 papers
  • Gang Cao — 4 papers
  • Gang Cao — 1 paper, h 4

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 citedExploring Multi-view Pixel Contrast for General and Robust Image Forgery Localization

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

collaborators

4 papers

cs.CV2024

Video Inpainting Localization with Contrastive Learning

Zijie Lou, Gang Cao, Man Lin

Deep video inpainting is typically used as malicious manipulation to remove important objects for creating fake videos. It is significant to identify the inpainted regions blindly.…

cs.CV2024★ 2 cited

Exploring Multi-view Pixel Contrast for General and Robust Image Forgery Localization

Zijie Lou, Gang Cao, Kun Guo +2

Image forgery localization, which aims to segment tampered regions in an image, is a fundamental yet challenging digital forensic task. While some deep learning-based forensic meth…

cs.CV2023

Spatio-temporal Co-attention Fusion Network for Video Splicing Localization

Man Lin, Gang Cao, Zijie Lou

Digital video splicing has become easy and ubiquitous. Malicious users copy some regions of a video and paste them to another video for creating realistic forgeries. It is signific…

cs.CV2023

Effective Image Tampering Localization via Enhanced Transformer and Co-attention Fusion

Kun Guo, Haochen Zhu, Gang Cao

Powerful manipulation techniques have made digital image forgeries be easily created and widespread without leaving visual anomalies. The blind localization of tampered regions bec…

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