Papers with Code 아카이브
Video Object Segmentation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Video object segmentation is a binary labeling problem aiming to separate foreground object(s) from the background region of a video.
For leaderboards please refer to the different subtasks.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/yujun0-0/mma-net
공식 코드VIL-100: A New Dataset and A Baseline Model for Video Instance Lane Detection
https://github.com/yuk6heo/GIS-RAmap
공식 코드Guided Interactive Video Object Segmentation Using Reliability-Based Attention Maps
https://github.com/yuk6heo/IVOS-ATNet
공식 코드Interactive Video Object Segmentation Using Global and Local Transfer Modules
https://github.com/yunkezhang/TCVOM
공식 코드https://github.com/yunongLiu1/IKEA-Manuals-at-Work
공식 코드IKEA Manuals at Work: 4D Grounding of Assembly Instructions on Internet Videos
https://github.com/yz93/anchor-diff-VOS
공식 코드https://github.com/z-x-yang/AOT
공식 코드Associating Objects with Transformers for Video Object Segmentation
https://github.com/z-x-yang/CFBI
공식 코드Collaborative Video Object Segmentation by Foreground-Background Integration
https://github.com/zamling/psalm
공식 코드https://github.com/zaplm/dc-sam
공식 코드DC-SAM: In-Context Segment Anything in Images and Videos via Dual Consistency
https://github.com/zhaoxing2022/mmn-vsod
공식 코드Motion-aware Memory Network for Fast Video Salient Object Detection
https://github.com/zhiweihhh/cvpr2022-rvos-challenge
공식 코드1st Place Solution for YouTubeVOS Challenge 2022: Referring Video Object Segmentation
https://github.com/zht8506/qmvos
공식 코드https://github.com/zihangm/Differentiable-LP-Layer
공식 코드Physarum Powered Differentiable Linear Programming Layers and Applications
https://github.com/zihangm/Physarum-Differentiable-LP-Layer
공식 코드Physarum Powered Differentiable Linear Programming Layers and Applications
https://github.com/zlai0/CorrFlow
공식 코드https://github.com/zlai0/MAST
공식 코드https://github.com/zrrskywalker/personalize-sam
공식 코드https://github.com/zwbx/DFM-Net
공식 코드Depth Quality-Inspired Feature Manipulation for Efficient RGB-D and Video Salient Object Detection
https://github.com/zzy-zhou/dsec-mos
공식 코드Event-Free Moving Object Segmentation from Moving Ego Vehicle
https://github.com/2023-MindSpore-1/ms-code-215/tree/main/OSVOS
https://github.com/2023-MindSpore-4/Code5/tree/main/D2Co
https://github.com/9p15p/frtm-vos
Learning Fast and Robust Target Models for Video Object Segmentation
https://github.com/AyaLotfy/PReMVOS-trial
PReMVOS: Proposal-generation, Refinement and Merging for Video Object Segmentation
https://github.com/AyaLotfy/premvos-tmp
PReMVOS: Proposal-generation, Refinement and Merging for Video Object Segmentation
https://github.com/BR-IDL/PaddleViT/tree/develop/self_supervised_learning/dino
https://github.com/BehradToghi/ConvLSTM_VOS
https://github.com/BehradToghi/ECCV_Youtube_VOS
https://github.com/DengPingFan/DAVSOD
https://github.com/DengPingFan/Inf-Net
https://github.com/EquipoVandV/mmactionVandV
Rethinking Self-supervised Correspondence Learning: A Video Frame-level Similarity Perspective
https://github.com/Expedit-LargeScale-Vision-Transformer/Expedit-DINO
https://github.com/FaceOnLive/Realtime-Background-Changer-SDK-Android
UniRef++: Segment Every Reference Object in Spatial and Temporal Spaces
https://github.com/GCVCG/VolETA-MetaFood
XMem++: Production-level Video Segmentation From Few Annotated Frames
https://github.com/GLUS-video/GLUS
GLUS: Global-Local Reasoning Unified into A Single Large Language Model for Video Segmentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.