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Foreground Segmentation
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/DLR-RM/DistinctNet
공식 코드"What's This?" -- Learning to Segment Unknown Objects from Manipulation Sequences
https://github.com/KAIST-Visual-AI-Group/PartSTAD
공식 코드https://github.com/ai4colonoscopy/pranet-v2
공식 코드PraNet-V2: Dual-Supervised Reverse Attention for Medical Image Segmentation
https://github.com/amirbar/visual_prompting
공식 코드https://github.com/casia-iva-lab/zbs
공식 코드https://github.com/dandingbudanding/DRSNet
공식 코드A De-raining semantic segmentation network for real-time foreground segmentation
https://github.com/dinghow/uim
공식 코드Exploring the Interactive Guidance for Unified and Effective Image Matting
https://github.com/duooppa/AquaSAM
공식 코드https://github.com/duwt/OrienMask
공식 코드Real-time Instance Segmentation with Discriminative Orientation Maps
https://github.com/geshang777/FOCUS
공식 코드https://github.com/geshang777/Seg-R1
공식 코드Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning
https://github.com/jackieam/e-inmemo
공식 코드https://github.com/jackieam/inmemo
공식 코드Instruct Me More! Random Prompting for Visual In-Context Learning
https://github.com/kleinzcy/csfpn
공식 코드Cascaded Sparse Feature Propagation Network for Interactive Segmentation
https://github.com/kormachine/partstad
공식 코드https://github.com/lids-unicamp/rethinking-interactive-image-segmentation
공식 코드Rethinking Interactive Image Segmentation: Feature Space Annotation
https://github.com/lim-anggun/FgSegNet
공식 코드Foreground Segmentation Using a Triplet Convolutional Neural Network for Multiscale Feature Encoding
https://github.com/lim-anggun/FgSegNet_v2
공식 코드https://github.com/mic-dkfz/foreground-and-anonymization-area-segmentation
공식 코드A Unified Framework for Foreground and Anonymization Area Segmentation in CT and MRI Data
https://github.com/michaelisc/cluttered-omniglot
공식 코드https://github.com/nifangbaage/explicit-visual-prompt
공식 코드Explicit Visual Prompting for Low-Level Structure Segmentations
https://github.com/plstcharles/litiv
공식 코드Online Mutual Foreground Segmentation for Multispectral Stereo Videos
https://github.com/shrubb/latent-pose-reenactment
공식 코드https://github.com/zju-vipa/BKT
공식 코드Visual Boundary Knowledge Translation for Foreground Segmentation
https://github.com/2023-MindSpore-1/ms-code-215/tree/main/OSVOS
https://github.com/MS-Mind/MS-Code-06/tree/main/OSVOS
https://github.com/Mind23-2/MindCode-5/tree/main/OSVOS
https://github.com/code-implementation1/Code6/tree/main/OSVOS
https://github.com/dksakkos/illumination_augmentation
Illumination-Based Data Augmentation for Robust Background Subtraction
https://github.com/jkvt2/Latent-Pose-Descriptors
https://github.com/kmaninis/OSVOS-PyTorch
https://github.com/kmaninis/OSVOS-caffe
https://github.com/nifangbaage/explict-visual-prompt
Explicit Visual Prompting for Universal Foreground Segmentations
https://github.com/scaelles/OSVOS-TensorFlow
https://github.com/xiuyu0000/new_papers_codes/tree/main/OSVOS
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.