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longxiang-ai/README.md

Hi, I'm Mingwei Li (李明伟) 👋

Zhejiang University Generative Visual Intelligence Research Focus

I am a third-year Ph.D. student in Artificial Intelligence at Zhejiang University, advised by Prof. Yi Yang. I am also a research intern at ByteDance, working on video generation and editing.

My research centers on generative visual intelligence, with a particular interest in connecting visual generation with geometry. My work spans controllable image and video generation, 3D vision, transparent-object geometry estimation, Gaussian Splatting, and digital human reconstruction and generation.

🔬 Research Interests

  • Video Generation and Editing — generative modeling, RGBA generation, visual understanding, and controllable content creation
  • Controllable Image Generation — multi-condition alignment and fine-grained instance control
  • 3D Vision and Gaussian Splatting — transparent-surface reconstruction and efficient neural rendering
  • Geometry Estimation — surface normal and depth estimation for challenging real-world materials
  • Digital Humans — efficient reconstruction, generation, and real-time rendering

📰 News

  • May 2026 — TransNormal was accepted to ICML 2026.
  • Jan 2026 — BideDPO was accepted to ICLR 2026.
  • May 2025 — DreamRenderer was accepted to ICCV 2025.
  • July 2025 — TSGS was accepted to ACM Multimedia 2025 as an Oral Presentation.

📚 Selected Publications

Mingwei Li, Hehe Fan, Yi Yang
ICML 2026
PDF GitHub

Single-step transparent-object surface normal estimation with dense visual semantics and diffusion priors.

Dewei Zhou, Mingwei Li, Zongxin Yang, Yu Lu, Yunqiu Xu, Zhizhong Wang, Zeyi Huang, Yi Yang
ICLR 2026
PDF GitHub

A bidirectionally decoupled preference optimization framework for resolving conflicts between text and visual conditions.

Dewei Zhou, Mingwei Li, Zongxin Yang, Yi Yang
ICCV 2025
PDF GitHub

A training-free controller for precise multi-instance attribute binding in large-scale text-to-image models.

Mingwei Li, Pu Pang, Hehe Fan, Hua Huang, Yi Yang
ACM Multimedia 2025 Oral
PDF GitHub

A two-stage Gaussian Splatting framework for geometrically accurate and photorealistic transparent-surface reconstruction.

Mingwei Li, Jiachen Tao, Zongxin Yang, Yi Yang
PDF GitHub

Fast monocular dynamic-human reconstruction with 100+ FPS rendering and training completed in hundreds of seconds.

🏆 Selected Honor

  • National First Prize, Huawei Cup Graduate AI Innovation Competition — Team Leader, 4th of 2,618 teams (Top 0.15%), 2024

📫 Contact

Email Homepage GitHub

📊 GitHub Activity

GitHub profile details

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  1. TSGS TSGS Public

    🎉 Official code release of "TSGS: Improving Gaussian Splatting for Transparent Surface Reconstruction via Normal and De-lighting Priors" (ACM MM 2025).

    Python 125 4

  2. Human101 Human101 Public

    The official implementation of "Human101: Training 100+FPS Human Gaussians in 100s from 1 View".

    110 2

  3. awesome-gaussians awesome-gaussians Public

    This repository tracks the latest advancements in 3D Gaussian Splatting from Arxiv, with daily automated updates. Stay up-to-date with cutting-edge research in this exciting field!

    Python 335 27

  4. pansanity666/Awesome-Avatars pansanity666/Awesome-Avatars Public

    List of recent advances for human avatars, including generation, reconstruction, and editing, etc.

    276 15

  5. TransNormal TransNormal Public

    Official implementation of "TransNormal: Dense Visual Semantics for Diffusion-based Transparent Object Normal Estimation" (ICML 2026). Single-step diffusion model for accurate surface normal predic…

    Python 20

  6. awesome-video-diffusions awesome-video-diffusions Public

    A curated and auto-updated collection of video diffusion / video generation papers from arXiv, covering text-to-video, image-to-video, controllable generation, world models, video editing, and 16+ …

    Python 37 2