Clement Fuji Tsang — accepted AI-conference papers

2026

VoMP: Predicting Volumetric Mechanical Property Fields

Rishit Dagli, Donglai Xiang, Vismay Modi, Charles Loop, Clement Fuji Tsang, Anka He Chen +4

ICLR 2026poster

Physical simulation relies on spatially-varying mechanical properties, typically laboriously hand-crafted. We present the first feed-forward model to predict fine-grained mechanical properties, Young’s modulus($E$), Poisson’s ratio($\nu$), and density($\rho$), throughout *the volume* of 3D objects.…

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2021

DIB-R++: Learning to Predict Lighting and Material with a Hybrid Differentiable Renderer

Wenzheng Chen, Joey Litalien, Jun Gao, Zian Wang, Clement Fuji Tsang, Sameh Khamis +2

NeurIPS 2021poster

We consider the challenging problem of predicting intrinsic object properties from a single image by exploiting differentiable renderers. Many previous learning-based approaches for inverse graphics adopt rasterization-based renderers and assume naive lighting and material models, which often fail t…

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