Siyou Lin

I am currently a PhD student at the Department of Automation, Tsinghua University, China, supervised by Prof. Yebin Liu. Prior to this, I received my Bachelor's degree in Mathematics from Tsinghua University.

We present Winding Number Normal Consistency (WNNC) and an iterative algorithm that estimates globally consistent normal vectors. Our CUDA-based treecode-accelerated algorithm handles a million of points in half a minute.

We present LayGA, a layered Gaussian avatar model based on Animatable Gaussians, with improved geometry and the ability of animatable clothing transfer.

We leverage intrinsic manifold properties and neural deformation fields and propose a coarse-to-fine two-stage method for non-rigid garment alignment, achieving wrinkle-level and texture-level alignment.

We present CaPhy, a novel method combining 3D-supervised training with unsupervised physics-based losses for reconstructing animatable human avatars. Caphy allows estimating the physical properties of garments and producing realistic dynamic clothing.

We present CloSET, a point-based human avatar modeling method that allows loose clothing modeling by explicit template decomposition. We also release a real-world capture dataset of clothed humans in various poses.

We propose a First-Implicit-Then-Explicit (FITE) framework that combines the merits of both implicit and explicit representations for modeling human avatars in clothing.

We present Parametric Gauss Reconstruction (PGR), a method that reconstructs surfaces from point clouds without normals by parametrizing the Gauss formula.

*Work done while I was an undergraduate at the Department of Mathematical Sciences, Tsinghua University.

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