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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 110 of 42 papers

TitleStatusHype
A Comprehensive Survey on Video Scene Parsing:Advances, Challenges, and Prospects0
MM-OR: A Large Multimodal Operating Room Dataset for Semantic Understanding of High-Intensity Surgical EnvironmentsCode2
LiDAR-Camera Fusion for Video Panoptic Segmentation without Video Training0
Balancing Shared and Task-Specific Representations: A Hybrid Approach to Depth-Aware Video Panoptic Segmentation0
MGNiceNet: Unified Monocular Geometric Scene UnderstandingCode0
Configurable Embodied Data Generation for Class-Agnostic RGB-D Video Segmentation0
Context-Aware Video Instance SegmentationCode2
Uni-DVPS: Unified Model for Depth-Aware Video Panoptic SegmentationCode1
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
3rd Place Solution for PVUW Challenge 2024: Video Panoptic Segmentation0
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