187 citations · 577 across the 14 of their papers we have counts for
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Hierarchical Neural Implicit Pose Network for Animation and Motion Retargeting
Sourav Biswas, Kangxue Yin, Maria Shugrina +2
We present HIPNet, a neural implicit pose network trained on multiple subjects across many poses. HIPNet can disentangle subject-specific details from pose-specific details, effect…
Deep Marching Tetrahedra: a Hybrid Representation for High-Resolution 3D Shape Synthesis
Tianchang Shen, Jun Gao, Kangxue Yin +2
We introduce DMTet, a deep 3D conditional generative model that can synthesize high-resolution 3D shapes using simple user guides such as coarse voxels. It marries the merits of im…
3DStyleNet: Creating 3D Shapes with Geometric and Texture Style Variations
Kangxue Yin, Jun Gao, Maria Shugrina +2
We propose a method to create plausible geometric and texture style variations of 3D objects in the quest to democratize 3D content creation. Given a pair of textured source and ta…
DatasetGAN: Efficient Labeled Data Factory with Minimal Human Effort
Yuxuan Zhang, Huan Ling, Jun Gao +5
We introduce DatasetGAN: an automatic procedure to generate massive datasets of high-quality semantically segmented images requiring minimal human effort. Current deep networks are…
Neural Geometric Level of Detail: Real-time Rendering with Implicit 3D Shapes
Towaki Takikawa, Joey Litalien, Kangxue Yin +6
Neural signed distance functions (SDFs) are emerging as an effective representation for 3D shapes. State-of-the-art methods typically encode the SDF with a large, fixed-size neural…