Zhengbo Xu — accepted AI-conference papers

2026

MoCha: End-to-End Video Character Replacement without Structural Guidance

Zhengbo Xu, Jie Ma, Ziheng Wang, Zhan Peng, Jun Liang, Jing Li

CVPR 2026

Controllable video character replacement with a user-provided identity remains a challenging problem due to the lack of paired video data. Prior works have predominantly relied on a reconstruction-based paradigm that requires per-frame segmentation masks and explicit structural guidance (e.g., skele

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2024

Frequency-Controlled Diffusion Model for Versatile Text-Guided Image-to-Image Translation

Xiang Gao, Zhengbo Xu, Junhan Zhao, Jiaying Liu

AAAI 2024technical

Recently, text-to-image diffusion models have emerged as a powerful tool for image-to-image translation (I2I), allowing flexible image translation via user-provided text prompts. This paper proposes frequency-controlled diffusion model (FCDiffusion), an end-to-end diffusion-based framework contribut…

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