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Video Panoptic Segmentation

Video Panoptic Segmentation is a computer vision task that extends panoptic segmentation by incorporating temporal dimension. That is, given a video sequence, the goal is to predict the semantic class of each pixel while consistently tracking object instances. Here, the pixels belonging to the same object instance should be assigned the same instance ID throughout the video sequence.

Papers

Showing 2642 of 42 papers

TitleStatusHype
Learning to Associate Every Segment for Video Panoptic Segmentation0
Hybrid Tracker with Pixel and Instance for Video Panoptic Segmentation0
SANPO: A Scene Understanding, Accessibility and Human Navigation Dataset0
Slot-VPS: Object-centric Representation Learning for Video Panoptic Segmentation0
1st Place Winner of the 2024 Pixel-level Video Understanding in the Wild (CVPR'24 PVUW) Challenge in Video Panoptic Segmentation and Best Long Video Consistency of Video Semantic Segmentation0
Configurable Embodied Data Generation for Class-Agnostic RGB-D Video Segmentation0
Time-Space Transformers for Video Panoptic Segmentation0
Balancing Shared and Task-Specific Representations: A Hybrid Approach to Depth-Aware Video Panoptic Segmentation0
Automated processing of X-ray computed tomography images via panoptic segmentation for modeling woven composite textiles0
An End-to-End Trainable Video Panoptic Segmentation Method usingTransformers0
Unified Perception: Efficient Depth-Aware Video Panoptic Segmentation with Minimal Annotation Costs0
A Comprehensive Survey on Video Scene Parsing:Advances, Challenges, and Prospects0
Video-kMaX: A Simple Unified Approach for Online and Near-Online Video Panoptic Segmentation0
3rd Place Solution for PVUW Challenge 2024: Video Panoptic Segmentation0
3rd Place Solution for PVUW Challenge 2023: Video Panoptic Segmentation0
Merging Tasks for Video Panoptic Segmentation0
2nd Place Solution for PVUW Challenge 2024: Video Panoptic Segmentation0
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