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UVO Challenge on Video-based Open-World Segmentation 2021: 1st Place Solution

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arxiv 2110.11661 v2 pith:ZDIU6BPZ submitted 2021-10-22 cs.CV

Yuming Du , Wen Guo , Yang Xiao , Vincent Lepetit This is my paper · ORCID
classification cs.CV
keywords instancesegmentationmaskchallengefirstmatchingopen-worldplace
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In this report, we introduce our (pretty straightforard) two-step "detect-then-match" video instance segmentation method. The first step performs instance segmentation for each frame to get a large number of instance mask proposals. The second step is to do inter-frame instance mask matching with the help of optical flow. We demonstrate that with high quality mask proposals, a simple matching mechanism is good enough for tracking. Our approach achieves the first place in the UVO 2021 Video-based Open-World Segmentation Challenge.

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  1. VideoAnydoor: High-fidelity Video Object Insertion with Precise Motion Control

    cs.CV 2025-01 conditional novelty 6.0 of 10

    A zero-shot diffusion framework that inserts a reference object into a video with high-fidelity appearance preservation and precise key-point trajectory motion control.

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