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Video Panoptic Segmentation On Vipseg

Metrics

STQ
VPQ

Results

Performance results of various models on this benchmark

Paper Title
CAVIS(VIT-L)56.158.5Context-Aware Video Instance Segmentation
MaXTron (ConvNeXtV2-L)-58.0A Simple Video Segmenter by Tracking Objects Along Axial Trajectories
DVIS++(VIT-L)56.058.0DVIS++: Improved Decoupled Framework for Universal Video Segmentation
DVIS(Swin-L)55.357.6DVIS: Decoupled Video Instance Segmentation Framework
MaXTron (ConvNeXt-L)-57.1A Simple Video Segmenter by Tracking Objects Along Axial Trajectories
DEVA (Mask2Former - SwinB)52.255.0Tracking Anything with Decoupled Video Segmentation
Tube-Link(Swin-base)49.450.4Tube-Link: A Flexible Cross Tube Framework for Universal Video Segmentation
UniVS(Swin-L)58.249.3UniVS: Unified and Universal Video Segmentation with Prompts as Queries
TarViS (Swin-L)52.948.0TarViS: A Unified Approach for Target-based Video Segmentation
MaXTron (ResNet-50)-46.7A Simple Video Segmenter by Tracking Objects Along Axial Trajectories
TarViS (Swin-T)45.335.8TarViS: A Unified Approach for Target-based Video Segmentation
TarViS (ResNet-50)43.133.5TarViS: A Unified Approach for Target-based Video Segmentation
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Video Panoptic Segmentation On Vipseg | SOTA | HyperAI