mlsanityData to 7 Oct 2026

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

arXiv 2306.04091 ↗First posted 7 Jun 2023cs.CVcited by 7

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Abstract (arXiv)

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

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 19 of its 23 references that are in the map. First posted on arXiv 7 Jun 2023.

Builds on

19 of 23 references.

References · 19

  1. 2017Attention Is All You Needcited by 59,932
  2. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  3. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,082
  4. 2021Masked-attention Mask Transformer for Universal Image Segmentationcited by 2,338
  5. 2019Video Instance Segmentationcited by 391
  6. 2019Panoptic-DeepLabcited by 362
  7. 2021K-Net: Towards Unified Image Segmentationcited by 211
  8. 2019UPSNet: A Unified Panoptic Segmentation Networkcited by 175
  9. 2021Mask2Former for Video Instance Segmentationcited by 169
  10. 2020Video Panoptic Segmentationcited by 141
  11. 2022In Defense of Online Models for Video Instance Segmentationcited by 97
  12. 2020ViP-DeepLab: Learning Visual Perception with Depth-aware Video Panoptic Segmentationcited by 95
7 more
  1. 2022VITA: Video Instance Segmentation via Object Token Associationcited by 94
  2. 2022MinVIS: A Minimal Video Instance Segmentation Framework without Video-based Trainingcited by 94
  3. 2022Video K-Net: A Simple, Strong, and Unified Baseline for Video Segmentationcited by 79
  4. 2023DVIS: Decoupled Video Instance Segmentation Frameworkcited by 77
  5. 2022A Generalized Framework for Video Instance Segmentationcited by 52
  6. 2021Memory Based Video Scene Parsingcited by 3
  7. 2021Exploiting Spatial-Temporal Semantic Consistency for Video Scene Parsingcited by 2

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 2; 2024: 1; 2025: 3; 2026: 1.

7 papers.

  1. 2023CTVIS: Consistent Training for Online Video Instance Segmentationcited by 50
  2. 2023DVIS++: Improved Decoupled Framework for Universal Video Segmentationcited by 46
  3. 2025Are They the Same? Exploring Visual Correspondence Shortcomings of Multimodal LLMscited by 16
  4. 2025The 1st Solution for 7th LSVOS RVOS Track: SaSaSa2VAcited by 7
  5. 20254th PVUW MeViS 3rd Place Report: Sa2VAcited by 2
  6. 20242nd Place Solution for PVUW Challenge 2024: Video Panoptic Segmentationcited by 0
  7. 2026SaSaSaSa2VA: 2nd Place of the 5th PVUW MeViS-Text Trackcited by 0