5 citations · 6 across the 19 of their papers we have counts for
6 papers · 1 filter
Differentiable Visual Computing for Inverse Problems and Machine Learning
Andrew Spielberg, Fangcheng Zhong, Konstantinos Rematas +4
Originally designed for applications in computer graphics, visual computing (VC) methods synthesize information about physical and virtual worlds, using prescribed algorithms optim…
Hypernetworks for Generalizable BRDF Representation
Fazilet Gokbudak, Alejandro Sztrajman, Chenliang Zhou +3
In this paper, we introduce a technique to estimate measured BRDFs from a sparse set of samples. Our approach offers accurate BRDF reconstructions that are generalizable to new mat…
FrePolad: Frequency-Rectified Point Latent Diffusion for Point Cloud Generation
Chenliang Zhou, Fangcheng Zhong, Param Hanji +5
We propose FrePolad: frequency-rectified point latent diffusion, a point cloud generation pipeline integrating a variational autoencoder (VAE) with a denoising diffusion probabilis…
Neural Fields with Hard Constraints of Arbitrary Differential Order
Fangcheng Zhong, Kyle Fogarty, Param Hanji +6
While deep learning techniques have become extremely popular for solving a broad range of optimization problems, methods to enforce hard constraints during optimization, particular…
Perceptual Quality Assessment of NeRF and Neural View Synthesis Methods for Front-Facing Views
Hanxue Liang, Tianhao Wu, Param Hanji +4
Neural view synthesis (NVS) is one of the most successful techniques for synthesizing free viewpoint videos, capable of achieving high fidelity from only a sparse set of captured i…
Surf: Implicit Surface Reconstruction for Semi-Transparent and Thin Objects with Decoupled Geometry and Opacity
Tianhao Wu, Hanxue Liang, Fangcheng Zhong +4
Implicit surface representations such as the signed distance function (SDF) have emerged as a promising approach for image-based surface reconstruction. However, existing optimizat…