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20242026
most citedReenact Anything: Semantic Video Motion Transfer Using Motion-Textual Inversion

5 citations · 5 across the 11 of their papers we have counts for

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cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2025

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…

cs.CV2025

High-Fidelity Novel View Synthesis via Splatting-Guided Diffusion

Xiang Zhang, Yang Zhang, Lukas Mehl +2

Despite recent advances in Novel View Synthesis (NVS), generating high-fidelity views from single or sparse observations remains a significant challenge. Existing splatting-based a…

cs.CV2024★ 5 cited

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.…

cs.CV2024

BetterDepth: Plug-and-Play Diffusion Refiner for Zero-Shot Monocular Depth Estimation

Xiang Zhang, Bingxin Ke, Hayko Riemenschneider +5

By training over large-scale datasets, zero-shot monocular depth estimation (MDE) methods show robust performance in the wild but often suffer from insufficient detail. Although re…