https://github.com/silky1708/locate
공식 코드LOCATE: Self-supervised Object Discovery via Flow-guided Graph-cut and Bootstrapped Self-training
Papers with Code 아카이브
Video Semantic Segmentation
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The goal of video semantic segmentation is to assign a predefined class to each pixel in all frames of a video. This requires the model not only to predict accurate segmentation masks but also to ensure that these masks remain temporally consistent across frames. This task has broad applications in areas such as autonomous driving, medical video analysis, and AR/VR.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/simarkareer/unifiedvideoda
공식 코드We're Not Using Videos Effectively: An Updated Domain Adaptive Video Segmentation Baseline
https://github.com/simonzeng7108/video-swinunet
공식 코드Video-SwinUNet: Spatio-temporal Deep Learning Framework for VFSS Instance Segmentation
https://github.com/simplexsigil/omnifall-experiments
공식 코드OmniFall: A Unified Staged-to-Wild Benchmark for Human Fall Detection
https://github.com/skyworkai/daq-vs
공식 코드DVIS-DAQ: Improving Video Segmentation via Dynamic Anchor Queries
https://github.com/speedinghzl/CCNet
공식 코드https://github.com/spyflying/CMPC-Refseg
공식 코드Cross-Modal Progressive Comprehension for Referring Segmentation
https://github.com/stegmuel/croc
공식 코드CrOC: Cross-View Online Clustering for Dense Visual Representation Learning
https://github.com/steve-tod/stfc3
공식 코드Breaking Shortcut: Exploring Fully Convolutional Cycle-Consistency for Video Correspondence Learning
https://github.com/subtri/video_inference
공식 코드Semantic Video Segmentation : Exploring Inference Efficiency
https://github.com/suhwan-cho/FindTrack
공식 코드https://github.com/suhwan-cho/bmvos
공식 코드Pixel-Level Bijective Matching for Video Object Segmentation
https://github.com/suhwan-cho/tbd
공식 코드Tackling Background Distraction in Video Object Segmentation
https://github.com/suhwan-cho/tmo
공식 코드Treating Motion as Option to Reduce Motion Dependency in Unsupervised Video Object Segmentation
https://github.com/sydney0zq/PTSNet
공식 코드Proposal, Tracking and Segmentation (PTS): A Cascaded Network for Video Object Segmentation
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/tanveer81/boxvos
공식 코드https://github.com/tapall-ai/mevis_track_solution_2024
공식 코드https://github.com/tensorflow/models
공식 코드FEELVOS: Fast End-to-End Embedding Learning for Video Object Segmentation
https://github.com/tfzhou/MATNet
공식 코드Motion-Attentive Transition for Zero-Shot Video Object Segmentation
https://github.com/tfzhou/vs-survey
공식 코드https://github.com/theevann/fast-cwm-segmentation
공식 코드Borrowing from yourself: Faster future video segmentation with partial channel update
https://github.com/thu-lyj-lab/ar-seg
공식 코드Efficient Semantic Segmentation by Altering Resolutions for Compressed Videos
https://github.com/ufukertenli/streamdeq-code
공식 코드https://github.com/umdatasciencelab/personalized_pca
공식 코드https://github.com/uncbiag/livos
공식 코드LiVOS: Light Video Object Segmentation with Gated Linear Matching
https://github.com/ut-vision/actionvos
공식 코드https://github.com/uva-dsa/runtime_robscene_seg_2context
공식 코드Robotic Scene Segmentation with Memory Network for Runtime Surgical Context Inference
https://github.com/uverma/ManipalUAVid
공식 코드UVid-Net: Enhanced Semantic Segmentation of UAV Aerial Videos by Embedding Temporal Information
https://github.com/v7labs/xmem_icl
공식 코드Flexible visual prompts for in-context learning in computer vision
https://github.com/verashira/TSPNet
공식 코드TSPNet: Hierarchical Feature Learning via Temporal Semantic Pyramid for Sign Language Translation
https://github.com/visinf/dense-ulearn-vos
공식 코드https://github.com/visionml/pytracking
공식 코드https://github.com/vitae-transformer/vos-llb
공식 코드https://github.com/vujas-eteph/lazyxmem
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.