https://github.com/epic-kitchens/visor-vos
공식 코드EPIC-KITCHENS VISOR Benchmark: VIdeo Segmentations and Object Relations
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/epic-kitchens/visor-wdtcf
공식 코드EPIC-KITCHENS VISOR Benchmark: VIdeo Segmentations and Object Relations
https://github.com/eraserNut/ViSha
공식 코드https://github.com/facebookresearch/Mask2Former
공식 코드https://github.com/facebookresearch/cutler
공식 코드VideoCutLER: Surprisingly Simple Unsupervised Video Instance Segmentation
https://github.com/facebookresearch/edgetam
공식 코드https://github.com/facebookresearch/sam2
공식 코드https://github.com/fatemehazimi990/HS2S
공식 코드Hybrid-S2S: Video Object Segmentation with Recurrent Networks and Correspondence Matching
https://github.com/fatemehazimi990/RS2S
공식 코드Revisiting Sequence-to-Sequence Video Object Segmentation with Multi-Task Loss and Skip-Memory
https://github.com/feipanir/moda
공식 코드https://github.com/foundationvision/uniref
공식 코드UniRef++: Segment Every Reference Object in Spatial and Temporal Spaces
https://github.com/fraunhoferivi/ssp
공식 코드https://github.com/genintel/datasetnerf
공식 코드DatasetNeRF: Efficient 3D-aware Data Factory with Generative Radiance Fields
https://github.com/griffbr/BubbleNets
공식 코드https://github.com/griffbr/ODMS
공식 코드Learning Object Depth from Camera Motion and Video Object Segmentation
https://github.com/griffbr/TIS
공식 코드https://github.com/griffbr/supervoxel-gerrymandering
공식 코드Video Object Segmentation using Supervoxel-Based Gerrymandering
https://github.com/guoleisun/vss-cffm
공식 코드Learning Local and Global Temporal Contexts for Video Semantic Segmentation
https://github.com/guoleisun/vss-mrcfa
공식 코드Mining Relations among Cross-Frame Affinities for Video Semantic Segmentation
https://github.com/haochenheheda/SwiftNet
공식 코드https://github.com/happy-hsy/motionmae
공식 코드Self-supervised Video Representation Learning with Motion-Aware Masked Autoencoders
https://github.com/harkiratbehl/MetaVOS
공식 코드Meta Learning Deep Visual Words for Fast Video Object Segmentation
https://github.com/hashmatshadab/apr
공식 코드Adversarial Pixel Restoration as a Pretext Task for Transferable Perturbations
https://github.com/hebeifast/eventlowlightvos
공식 코드https://github.com/henghuiding/MOSE-api
공식 코드MOSE: A New Dataset for Video Object Segmentation in Complex Scenes
https://github.com/henghuiding/MeViS
공식 코드MeViS: A Large-scale Benchmark for Video Segmentation with Motion Expressions
https://github.com/hengliusky/few_shot_rvos
공식 코드Learning Cross-Modal Affinity for Referring Video Object Segmentation Targeting Limited Samples
https://github.com/heshuting555/dshmp
공식 코드Decoupling Static and Hierarchical Motion Perception for Referring Video Segmentation
https://github.com/hiltonml/camera_trap_tools
공식 코드An Image Processing Pipeline for Camera Trap Time-Lapse Recordings
https://github.com/hkchengrex/Cutie
공식 코드https://github.com/hkchengrex/MiVOS
공식 코드https://github.com/hkchengrex/STCN
공식 코드Rethinking Space-Time Networks with Improved Memory Coverage for Efficient Video Object Segmentation
https://github.com/hkchengrex/Tracking-Anything-with-DEVA
공식 코드https://github.com/hkchengrex/XMem
공식 코드XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model
https://github.com/hongje/hmmn
공식 코드Hierarchical Memory Matching Network for Video Object Segmentation
https://github.com/hszhao/PSPNet
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.