Cheng Lin @_cheng_lin
Research Scientist | Ph.D. @HKUniversity | Organizer @AnySyn3D 3D Vision, 3D AIGC, Geometric Modeling, Graphics clinplayer.github.io Joined March 2020-
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Excited that 🎧MOSPA: Human Motion Generation Driven by Spatial Audio was accepted as a #NeurIPS2025 Spotlight! ✨ We hope #MOSPA can advance motion generation toward spatial intelligence a bit more, and also inspire progress in humanoid control and embodied AI. 🎧🏃♀️➡️ We’ll…
Excited that 🎧MOSPA: Human Motion Generation Driven by Spatial Audio was accepted as a #NeurIPS2025 Spotlight! ✨ We hope #MOSPA can advance motion generation toward spatial intelligence a bit more, and also inspire progress in humanoid control and embodied AI. 🎧🏃♀️➡️ We’ll…
Check out our #ICCV2025 paper VertexRegen! Instead of the typical incomplete meshes you get with autoreg mesh gen, VertexRegen generates progressively more detailed meshes as the generated sequence gets longer. vertexregen.github.io Great work by xzhang.dev
We are excited to announce our PDT: Point Distribution Transformation with Diffusion Models, to appear in SIGGRAPH 2025! Paper link: arxiv.org/abs/2507.18939 Project page: shanemankiw.github.io/PDT/
Check out Spatial Audio-drive Human Motion Generation. This will be very useful for future interactions with virtual AI characters in spatial environment!
Check out Spatial Audio-drive Human Motion Generation. This will be very useful for future interactions with virtual AI characters in spatial environment!
📢 LiteReality: Graphics-Ready 3D Scene Reconstruction from RGB-D Scans🏠✨ -> converts RGB-D scans into compact, realistic, and interactive 3D scenes — featuring high-quality meshes, PBR materials, and articulated objects. 📷youtu.be/ecK9m3LXg2c 🌍litereality.github.io
Check out Gaussian-enhanced Surfels (GESs) from Zhejiang University! A novel bi-scale radiance field representation combining 2D opaque surfels (coarse geometry) with 3D Gaussians (fine details). Fast, sorting-free rendering with high fidelity and view consistency.
[SIGGRAPH '25] When Gaussian Meets Surfel: Ultra-fast High-fidelity Radiance Field Rendering • The introduction of Gaussian-enhanced Surfels (GESs), the first representation that combines the surfel radiance field with the Gaussian radiance field, achieving ultra-fast…
Presenting GAF at #CVPR2025 📢📢 If you'd like to discuss Gaussian Avatar Reconstruction and Multi-view Diffusion, come visit our poster on Friday, June 13th, in ExHall D between 16:00-18:00 (Poster #10). Project Page:tangjiapeng.github.io/projects/GAF/
📅Call for Papers: Special Issue on "Controllable Artificial Intelligence Visual Content Generation"📊💡 Submit your work on controllable AI-driven visual content generation for the SI! Deadline: 31 August 2025 Deails: link.springer.com/collections/gb… #controllableAI #AIGC #CallForPapers
Walking around a massive 3d gaussian splat is pretty cool. Game engines and even web apps can give you physics interactions + the beauty of a radiance field. Need to enrich it with more semantic data and other agents to bring this world to life.
Excited to share our work DrivingWorld, a GPT-style Autoregressive (AR) video world model for autonomous driving. Rather than simply employ the next-token-prediction strategy, we leverage next-frame-prediction to model temporally coherent frame-wise information and then use…
ChatGarment connects language, vision, and garment sewing pattern via LLAVA.
Super interesting idea
Our new work PSHuman reconstructs a detailed 3D human mesh from a single-view image in ~1min. Codes have already been released! Welcome to try it! Project page: penghtyx.github.io/PSHuman/ Codes: github.com/pengHTYX/PSHum… Paper: arxiv.org/abs/2409.10141
3D-LLM: Injecting the 3D World into Large Language Models paper page: huggingface.co/papers/2307.12… Large language models (LLMs) and Vision-Language Models (VLMs) have been proven to excel at multiple tasks, such as commonsense reasoning. Powerful as these models can be, they are not…
#SIGGRAPHASIA #SIGGRAPHASIA2024 #ACMTOG 🐟 We introduce Collective Behavior Imitation Learning (CBIL), a scalable, self-supervised framework for learning fish schooling behaviors from videos, to be presented at SIGGRAPH ASIA 2024 Tokyo (journal track)🗼! 🦈Reproducing realistic…
Yuan's amazing new work 🥰! Congrats!
Yuan's amazing new work 🥰! Congrats!

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AcadeMax Journals @Academax_J
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yao lu @yluAIinfra
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Ziyang Luo @ChiYeung_Law
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