Papers with Code 아카이브
Video Semantic Segmentation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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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/cy-xu/spatially_aware_ai
https://github.com/daveboat/spp
https://github.com/dcnieho/segment-anything-2
https://github.com/dipika-singhania/multi-scale-action-banks
Temporal Aggregate Representations for Long-Range Video Understanding
https://github.com/divamgupta/image-segmentation-keras
https://github.com/dongkwonjin/Semantic-Line-DRM
Interactive Video Object Segmentation Using Global and Local Transfer Modules
https://github.com/dongkwonjin/Semantic-Line-SLNet
Interactive Video Object Segmentation Using Global and Local Transfer Modules
https://github.com/dxli94/WLASL
TSPNet: Hierarchical Feature Learning via Temporal Semantic Pyramid for Sign Language Translation
https://github.com/emsalinha/videosum-eval
https://github.com/enot-autodl/lpcv-2023
https://github.com/facebookresearch/segment-anything
https://github.com/feinanshan/TDNet
Temporally Distributed Networks for Fast Video Semantic Segmentation
https://github.com/fenglian425/Agriculture_AI
https://github.com/fmahoudeau/fcn
https://github.com/foolwood/SiamMask
SiamMask: A Framework for Fast Online Object Tracking and Segmentation
https://github.com/geekswaroop/Human-Parsing
https://github.com/geodekid/FCN
https://github.com/griffbr/ODMD
Learning Object Depth from Camera Motion and Video Object Segmentation
https://github.com/griffbr/VOSVS
https://github.com/guanfuchen/video_obj
Fast and Accurate Online Video Object Segmentation via Tracking Parts
https://github.com/gunpowder78/PReMVOS
PReMVOS: Proposal-generation, Refinement and Merging for Video Object Segmentation
https://github.com/hgjeon/CarND-Semantic-Segmentation
https://github.com/hkchengrex/Mask-Propagation
https://github.com/hkchengrex/Scribble-to-Mask
https://github.com/holyseven/PSPNet-TF-Reproduce
https://github.com/huggingface/transformers
https://github.com/ibaiGorordo/ONNX-SAM2-Segment-Anything
https://github.com/idea-research/grounded-sam-2
https://github.com/idilesenzulfikar/UNOVOST
UnOVOST: Unsupervised Offline Video Object Segmentation and Tracking
https://github.com/insomnia94/ARG
Adaptive ROI Generation for Video Object Segmentation Using Reinforcement Learning
https://github.com/intelligent-vehicles/bevdriver
https://github.com/irfanICMLL/ETC-Real-time-Per-frame-Semantic-video-segmentation
Efficient Semantic Video Segmentation with Per-frame Inference
https://github.com/irfanICMLL/structure_knowledge_distillation
https://github.com/jiwei0921/MVSS-Baseline
https://github.com/joakimjohnander/agame-vos
A Generative Appearance Model for End-to-end Video Object Segmentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.