Jiafeng Mao

Jiafeng Mao

Research Scientist @ CyberAgent AI Lab

About Me

I am currently a research scientist at Cyberagent AI Lab. I worked as a project researcher with Aizawa Lab of The University of Tokyo, Japan.

My research interest is in Computer Vision, including controllable image generation and visual understanding.

Recently, I am focusing on Agentic AI, agentic visual content planning and generation, and cooperation with large-scale commercial models.

News

  • 2026.02:   1 paper is accepted by CVPR 2026
  • 2025.11:   1 paper is accepted by AAAI 2026
  • 2025.07:   1 paper is accepted by ICCV 2025 Workshop
  • 2025.07:   1 paper is accepted by ACM MM 2025
  • 2025.05:   2 papers are accepted by ICIP 2025

Featured Works

CVPR 2026
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Region-Wise Correspondence Prediction between Manga Line Art Images

Yingxuan Li, Jiafeng Mao, Qianru Qiu, Yusuke Matsui

  • Transformer-based Manga lineart region matching
  • Pseudo & Noisy Label learning
ECCV 2024
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The Lottery Ticket Hypothesis in Denoising: Towards Semantic-Driven Initialization

Jiafeng Mao, Xueting Wang, Kiyoharu Aizawa

  • Collecting noise pixel blocks to construct initial noise according to specified layout.
  • Comfirming versatility of noise blocks over prompts and images.
ACM MM 2023
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Guided Image Synthesis via Initial Image Editing in Diffusion Model

Jiafeng Mao, Xueting Wang, Kiyoharu Aizawa

  • Analyzing the generation tendency of intial noise
  • initial noise manipulation for generated image repainting and layout-to-image generation
arXiv 2025
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LORE: Latent Optimization for Precise Semantic Control in Rectified Flow-based Image Editing

Liangyang Ouyang, Jiafeng Mao

  • Analyzing the generation tendency issue in the image editing task
  • Inverted noise optimization for semantic control in RF-based image editing.
arXiv 2025
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MangaDiT: Reference-Guided Line Art Colorization with Hierarchical Attention in Diffusion Transformers

Qianru Qiu, Jiafeng Mao, Kento Masui, Xueting Wang

  • DiT-based Manga lineart colorization with a reference colorized image
  • Hierarchical Attention for Precise region matching