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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 31–40 of 42 papers

TitleStatusHype
Balancing Shared and Task-Specific Representations: A Hybrid Approach to Depth-Aware Video Panoptic Segmentation—0
Configurable Embodied Data Generation for Class-Agnostic RGB-D Video Segmentation—0
Hybrid Tracker with Pixel and Instance for Video Panoptic Segmentation—0
Learning to Associate Every Segment for Video Panoptic Segmentation—0
LiDAR-Camera Fusion for Video Panoptic Segmentation without Video Training—0
Merging Tasks for Video Panoptic Segmentation—0
MonoDVPS: A Self-Supervised Monocular Depth Estimation Approach to Depth-aware Video Panoptic Segmentation—0
PAg-NeRF: Towards fast and efficient end-to-end panoptic 3D representations for agricultural robotics—0
SANPO: A Scene Understanding, Accessibility and Human Navigation Dataset—0
Slot-VPS: Object-centric Representation Learning for Video Panoptic Segmentation—0
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