mlsanityData to 7 Oct 2026

PM-VIS+: High-Performance Video Instance Segmentation without Video Annotation

arXiv 2406.19665 ↗First posted 28 Jun 2024cs.CVcited by 0

Not on the map. Why?

Abstract (arXiv)

Video instance segmentation requires detecting, segmenting, and tracking objects in videos, typically relying on costly video annotations. This paper introduces a method that eliminates video annotations by utilizing image datasets. The PM-VIS algorithm is adapted to handle both bounding box and instance-level pixel annotations dynamically. We introduce ImageNet-bbox to supplement missing categories in video datasets and propose the PM-VIS+ algorithm to adjust supervision based on annotation types. To enhance accuracy, we use pseudo masks and semi-supervised optimization techniques on unannotated video data. This method achieves high video instance segmentation performance without manual video annotations, offering a cost-effective solution and new perspectives for video instance segmentation applications. The code will be available in https://github.com/ldknight/PM-VIS-plus

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 22 of its 26 references that are in the map. First posted on arXiv 28 Jun 2024.

Builds on

22 of 26 references.

References · 22

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,082
  3. 2020End-to-End Object Detection with Transformerscited by 7,384
  4. 2021Masked-attention Mask Transformer for Universal Image Segmentationcited by 2,338
  5. 2016V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentationcited by 2,284
  6. 2019Video Instance Segmentationcited by 391
  7. 2021Occluded Video Instance Segmentation: A Benchmarkcited by 154
  8. 2020BoxInst: High-Performance Instance Segmentation with Box Annotationscited by 150
  9. 2022Decoupling Features in Hierarchical Propagation for Video Object Segmentationcited by 146
  10. 2019Classifying, Segmenting, and Tracking Object Instances in Video with Mask Propagationcited by 125
  11. 2021SeqFormer: Sequential Transformer for Video Instance Segmentationcited by 98
  12. 2022In Defense of Online Models for Video Instance Segmentationcited by 97
10 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. 2021Pointly-Supervised Instance Segmentationcited by 83
  4. 2021Video Instance Segmentation with a Propose-Reduce Paradigmcited by 74
  5. 2021DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervisioncited by 59
  6. 2022A Generalized Framework for Video Instance Segmentationcited by 52
  7. 2023Mask-Free Video Instance Segmentationcited by 20
  8. 2021Weakly Supervised Instance Segmentation for Videos with Temporal Mask Consistencycited by 19
  9. 2023GRAtt-VIS: Gated Residual Attention for Auto Rectifying Video Instance Segmentationcited by 9
  10. 2024PM-VIS: High-Performance Box-Supervised Video Instance Segmentationcited by 2

Built on by

Not cited yet.