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arXiv Computer Vision By Yuetong Wang, Jinsheng Quan, Yi Yang, Yawei Luo

Bi-FlowGS: Bridging Generative View Completion and Gaussian Geometry through Bidirectional Flow Co-Refinement

Read the original on arXiv Computer Vision →

Bi-FlowGS introduces a bidirectional co-refinement framework that links generative view completion with 3D Gaussian Splatting geometry. It employs Video-to-Geometry Flow Distillation (V2G) to transfer temporal correspondence from restored videos into Gaussian geometry, mitigating the Geometry Cheating problem. Simultaneously, Geometry-to-Video Flow-Guided Restoration (G2V) uses the current 3DGS geometry to guide temporally consistent video restoration, creating a loop where restored videos and optimized geometry iteratively improve each other, leading to better rendering quality and geometric consistency on wide-baseline and 360° benchmarks.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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