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Han Fang

4 papers hereh-index 314 citations11 works total

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

author position
  • middle author4

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

fields
  • cs.CV3
  • cs.CR1
same name
  • Han Fang — 14 papers, h 18
  • Han Fang — 12 papers, h 8
  • Han Fang — 7 papers, h 5
  • Han Fang — 6 papers, h 3
  • Han Fang — 4 papers, h 1
  • Han Fang — 2 papers, h 3

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

works on
deep learning 1geometric robustness 1image watermarking 1spatial attention 1visual quality 1

From the 1 of 4 linked papers with an AI index.

collaborators

4 papers

cs.CV2026

CASIAL: Geometric Distortion Robust Image Watermarking

Yupeng Qiu, Han Fang, Ee-Chien Chang

The paper introduces CASIAL, a deep learning framework for image watermarking that spreads watermark bits across the whole image and uses a geometry‑invariant alignment module to s…

cs.CV2026

ResGuard: Enhancing Robustness Against Known Original Attacks in Deep Watermarking

Hanyi Wang, Han Fang, Yupeng Qiu +2

Deep learning-based image watermarking commonly adopts an "Encoder-Noise Layer-Decoder" (END) architecture to improve robustness against random channel distortions, yet it often ov…

cs.CR2026

Proof-of-Authorship for Diffusion-based AI Generated Content

De Zhang Lee, Han Fang, Ee-Chien Chang

Recent advancements in AI-generated content (AIGC) have introduced new challenges in intellectual property protection and the authentication of generated objects. We focus on scena…

cs.CV2024

END2: Robust Dual-Decoder Watermarking Framework Against Non-Differentiable Distortions

Nan Sun, Han Fang, Yuxing Lu +2

DNN-based watermarking methods have rapidly advanced, with the ``Encoder-Noise Layer-Decoder'' (END) framework being the most widely used. To ensure end-to-end training, the noise…

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