8 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…
Efficient All-Pairs Correlation Volume Sampling for Optical Flow Estimation
Karlis Martins Briedis, Markus Gross, Christopher Schroers
Recent optical flow estimation methods often employ local cost sampling from a dense all-pairs correlation volume. This results in quadratic computational and memory complexity in…
ConFixGS: Learning to Fix Feedforward 3D Gaussian Splatting with Confidence-Aware Diffusion Priors in Driving Scenes
Rui Song, Tianhui Cai, Markus Gross +5
Feedforward 3D Gaussian Splatting (3DGS) often struggles in trajectory-based sparse-view driving scenes. Existing Gaussian repair methods mainly target optimization-based 3DGS, whi…
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…
StableDPT: Temporal Stable Monocular Video Depth Estimation
Ivan Sobko, Hayko Riemenschneider, Markus Gross +1
Applying single image Monocular Depth Estimation (MDE) models to video sequences introduces significant temporal instability and flickering artifacts. We propose a novel approach t…
Reenact Anything: Semantic Video Motion Transfer Using Motion-Textual Inversion
Manuel Kansy, Jacek Naruniec, Christopher Schroers +2
Recent years have seen a tremendous improvement in the quality of video generation and editing approaches. While several techniques focus on editing appearance, few address motion.…