Jiaxu Zhang | 张嘉旭

I am a Ph.D. student working with Prof. Deren Li and Prof. Zhigang Tu in LIESMARS at Wuhan University, China. Before that, I received my B.S. degree from Southeast University in 2020 and MEng from Wuhan University in 2023.
I worked as a research intern at Tencent from 2022 to 2024. Currently, I am interning at StepFun, collaborating with Dr. Gang Yu on AIGC research. My research interest lies in deep learning, computer vision and computer graphics, with a current focus on 3D/2D animation, motion generation, retargeting, and recognition.

Expected graduation in 2026, open to postdoc and research scientist positions.

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We propose MikuDance, a diffusion-based pipeline incorporating mixed motion dynamics to animate stylized character art.

A project for transforming Genshin PVs into a freehand style using Diffusion Model.

I've been exploring 2D image animation recently. This project is purely for fun. Feel free to reach out and discuss this with me.

M-R2ET is a modular neural motion retargeting system designed to transfer motion between characters with different structures but corresponding to homeomorphic graphs, meanwhile preserving motion semantics and perceiving shape geometries.

We present MotionS, a generative motion stylization pipeline for synthesizing diverse and stylized motion on cross-structure source using cross-modality style prompts.

TapMo is a text-based animation pipeline for generating motion in a wide variety of skeleton-free characters.

R2ET is a neural motion retargeting model that can preserve the source motion semantics and avoid interpenetration in the target motion.

We propose a novel Zoom Transformer to exploit both the low-level single-person motion information and the high-level multi-person interaction information in a uniform attention structure.

we propose a semi-supervised skeleton-based action recognition method.