https://github.com/Ali2500/TarViS
공식 코드TarViS: A Unified Approach for Target-based Video Segmentation
Papers with Code 아카이브
Video Panoptic Segmentation
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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.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Seung-Hun-Lee/CAVIS
공식 코드https://github.com/egeozsoy/MM-OR
공식 코드https://github.com/google-research/deeplab2
공식 코드https://github.com/harboryuan/polyphonicformer
공식 코드PolyphonicFormer: Unified Query Learning for Depth-aware Video Panoptic Segmentation
https://github.com/hkchengrex/Tracking-Anything-with-DEVA
공식 코드https://github.com/idt-iti/xai-video-summaries
공식 코드An Integrated Framework for Multi-Granular Explanation of Video Summarization
https://github.com/joe-siyuan-qiao/ViP-DeepLab
공식 코드ViP-DeepLab: Learning Visual Perception with Depth-aware Video Panoptic Segmentation
https://github.com/lxtgh/tube-link
공식 코드Tube-Link: A Flexible Cross Tube Framework for Universal Video Segmentation
https://github.com/lxtgh/video-k-net
공식 코드Video K-Net: A Simple, Strong, and Unified Baseline for Video Segmentation
https://github.com/mcahny/vps
공식 코드https://github.com/minghanli/univs
공식 코드UniVS: Unified and Universal Video Segmentation with Prompts as Queries
https://github.com/tacju/axial-vs
공식 코드A Simple Video Segmenter by Tracking Objects Along Axial Trajectories
https://github.com/tacju/maxtron
공식 코드A Simple Video Segmenter by Tracking Objects Along Axial Trajectories
https://github.com/zhang-tao-whu/DVIS
공식 코드https://github.com/zhang-tao-whu/DVIS_Plus
공식 코드DVIS++: Improved Decoupled Framework for Universal Video Segmentation
https://github.com/zju3dv/PVO
공식 코드https://github.com/MindSpore-scientific/code-7/tree/main/GroupViT
ViP-DeepLab: Learning Visual Perception with Depth-aware Video Panoptic Segmentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.