5 papers · 1 filter
αDepth: Learning Single-Pass Soft Boundary Decomposition for Stereo Conversion
Xiang Zhang, Yang Zhang, Lukas Mehl +3
Accurately modeling soft boundaries, e.g., hair and defocus blur, is a fundamental challenge in stereo conversion due to the ambiguous blending of foreground and background. Existi…
UniFixer: A Universal Reference-Guided Fixer for Diffusion-Based View Synthesis
Sihan Chen, Xiang Zhang, Yang Zhang +2
With the recent surge of generative models, diffusion-based approaches have become mainstream for view synthesis tasks, either in an explicit depth-warp-inpaint or in an implicit e…
RenderFlow: Single-Step Neural Rendering via Flow Matching
Shenghao Zhang, Runtao Liu, Christopher Schroers +1
Conventional physically based rendering (PBR) pipelines generate photorealistic images through computationally intensive light transport simulations. Although recent deep learning…
Guardians of the Hair: Rescuing Soft Boundaries in Depth, Stereo, and Novel Views
Xiang Zhang, Yang Zhang, Lukas Mehl +2
Soft boundaries, like thin hairs, are commonly observed in natural and computer-generated imagery, but they remain challenging for 3D vision due to the ambiguous mixing of foregrou…
Spline Deformation Field
Mingyang Song, Yang Zhang, Marko Mihajlovic +3
Trajectory modeling of dense points usually employs implicit deformation fields, represented as neural networks that map coordinates to relate canonical spatial positions to tempor…