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20242026
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cs.CV2026

MegaFlow: Zero-Shot Large Displacement Optical Flow

Dingxi Zhang, Fangjinhua Wang, Marc Pollefeys +1

Accurate estimation of large displacement optical flow remains a critical challenge. Existing methods typically rely on iterative local search or/and domain-specific fine-tuning, w…

cs.CV2026

PointDiT: Pixel-Space Diffusion for Monocular Geometry Estimation

Haofei Xu, Rundi Wu, Philipp Henzler +7

State-of-the-art single-image 3D reconstruction methods often rely on complex hybrid architectures and loss functions, or compress geometry into latent spaces in order to leverage…

cs.CV2026

InvSplat: Inverse Feed-Forward Scene Splatting

Polina Karpikova, Wenjing Bian, Haofei Xu +2

Inverse rendering aims to recover both 3D geometry and physically meaningful material properties from images, enabling applications such as relighting and novel view synthesis. Opt…

cs.CV2026

Learn2Splat: Extending the Horizon of Learned 3DGS Optimization

Naama Pearl, Stefano Esposito, Haofei Xu +6

3D Gaussian Splatting (3DGS) optimization is most commonly performed using standard optimizers (Adam, SGD). While stable across diverse scenes, standard optimizers are general-purp…

cs.CV2026

Feed-Forward 3D Scene Modeling: A Problem-Driven Perspective

Weijie Wang, Qihang Cao, Sensen Gao +10

Reconstructing 3D representations from 2D inputs is a fundamental task in computer vision and graphics, serving as a cornerstone for understanding and interacting with the physical…

cs.CV2025

Explicit Correspondence Matching for Generalizable Neural Radiance Fields

Yuedong Chen, Haofei Xu, Qianyi Wu +3

We present a new generalizable NeRF method that is able to directly generalize to new unseen scenarios and perform novel view synthesis with as few as two source views. The key to…