1st Place Solution for PVUW Challenge 2023: Video Panoptic Segmentation

• URL: http://arxiv.org/abs/2306.04091v2
• Date: Thu, 8 Jun 2023 08:19:27 GMT
• Title: 1st Place Solution for PVUW Challenge 2023: Video Panoptic Segmentation
• Authors: Tao Zhang and Xingye Tian and Haoran Wei and Yu Wu and Shunping Ji and Xuebo Wang and Xin Tao and Yuan Zhang and Pengfei Wan
• Abstract summary: Video panoptic segmentation is a challenging task that serves as the cornerstone of numerous downstream applications. We believe that the decoupling strategy proposed by DVIS enables more effective utilization of temporal information for both "thing" and "stuff" objects. Our method achieved a VPQ score of 51.4 and 53.7 in the development and test phases, respectively, and ranked 1st in the VPS track of the 2nd PVUW Challenge.
• Score: 25.235404527487784
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Video panoptic segmentation is a challenging task that serves as the cornerstone of numerous downstream applications, including video editing and autonomous driving. We believe that the decoupling strategy proposed by DVIS enables more effective utilization of temporal information for both "thing" and "stuff" objects. In this report, we successfully validated the effectiveness of the decoupling strategy in video panoptic segmentation. Finally, our method achieved a VPQ score of 51.4 and 53.7 in the development and test phases, respectively, and ultimately ranked 1st in the VPS track of the 2nd PVUW Challenge. The code is available at https://github.com/zhang-tao-whu/DVIS

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