Peng Chen

I am a second-year master student at Institute of Software, Chinese Academy of Sciences, supervised by Prof. Hui Chen from ISCAS and Ming Lu from Intel Labs China. I received my B.S. in Computer Science from University of Science and Technology, Beijing in 2023 and obtained Beijing Distinguished Graduate Award and Beijing Outstanding Graduation Thesis.

I serve as a reviewer for international conferences including ICLR and ISMAR.

My research focuses on 3D Vision, AIGC, and VLM, involving technologies like 3DGS, Diffusion, LLaVA, and their derivatives, with applications in digital humans (3D face reconstruction and facial animation), image generation, VLA agent, and image/video understanding.

I am currently looking for a PhD position for Fall 2026.

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We use 2DGS to maintain the surface geometry and employ 3DGS for color correction in areas where the rendering quality of 2DGS is insufficient, reconstructing a realistically and geometrically accurate 3D head avatar.

We propose GazeGaussian, a high-fidelity gaze redirection method that uses a two-stream 3DGS model to represent the face and eye regions separately.

We propose GraphAvatar, a compact method using Graph Neural Networks (GNN) to generate 3D Gaussians for head avatar animation, offering superior rendering performance and minimal storage requirements.

We propose a novel framework named the VARP agent, which directly takes game screenshots as input and generates keyboard and mouse operations to play the ARPG.

We propose DiffusionTalker, a diffusion-based method that utilizes contrastive personalizer to generate personalized 3D facial animation and personalizer-guided distillation for acceleration and compression.

Given a target facial video as reference, bring your own character into our solution integrated with Unity3D, it automatically generates facial animation for the virtual character.