3 papers
cs.CV2026
SharpNet: Enhancing MLPs to Represent Functions with Controlled Non-differentiability
Hanting Niu, Junkai Deng, Fei Hou +2
Multi-layer perceptrons (MLPs) are a standard tool for learning and function approximation, but they inherently produce globally smooth outputs. Consequently, they struggle to repr…
cs.CV2025
Voronoi-Assisted Diffusion for Computing Unsigned Distance Fields from Unoriented Points
Jiayi Kong, Chen Zong, Junkai Deng +6
Unsigned Distance Fields (UDFs) provide a flexible representation for 3D shapes with arbitrary topology, including open and closed surfaces, orientable and non-orientable geometrie…
cs.CV2025
From Transparent to Opaque: Rethinking Neural Implicit Surfaces with -NeuS
Haoran Zhang, Junkai Deng, Xuhui Chen +5
Traditional 3D shape reconstruction techniques from multi-view images, such as structure from motion and multi-view stereo, face challenges in reconstructing transparent objects. R…