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Few-Shot Semantic Segmentation
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Few-shot semantic segmentation (FSS) learns to segment target objects in query image given few pixel-wise annotated support image.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/sam1224/hmnet
공식 코드https://github.com/sam1224/sccan
공식 코드Self-Calibrated Cross Attention Network for Few-Shot Segmentation
https://github.com/savinay95n/PatchRefineNet
공식 코드https://github.com/sha168/ADNet
공식 코드https://github.com/shadowxzt/dacm-few-shot.pytorch
공식 코드Doubly Deformable Aggregation of Covariance Matrices for Few-shot Segmentation
https://github.com/sinahmr/diam
공식 코드A Strong Baseline for Generalized Few-Shot Semantic Segmentation
https://github.com/syp2ysy/SVF
공식 코드Singular Value Fine-tuning: Few-shot Segmentation requires Few-parameters Fine-tuning
https://github.com/taveraantonio/pixda
공식 코드Pixel-by-Pixel Cross-Domain Alignment for Few-Shot Semantic Segmentation
https://github.com/theoceancleanup/rivertrashsegmentation
공식 코드Foundation Model or Finetune? Evaluation of few-shot semantic segmentation for river pollution
https://github.com/tinyaway/manet
공식 코드https://github.com/tntek/dspnet
공식 코드Few-Shot Medical Image Segmentation with High-Fidelity Prototypes
https://github.com/whileherham/imr-hsnet
공식 코드Iterative Few-shot Semantic Segmentation from Image Label Text
https://github.com/xiaomengyc/Few-Shot-Semantic-Segmentation-Papers
공식 코드https://github.com/xiaomengyc/SG-One
공식 코드SG-One: Similarity Guidance Network for One-Shot Semantic Segmentation
https://github.com/zbf1991/SCL
공식 코드Self-Guided and Cross-Guided Learning for Few-Shot Segmentation
https://github.com/zhangzilongc/sofs
공식 코드Small Object Few-shot Segmentation for Vision-based Industrial Inspection
https://github.com/zhiheLu/CWT-for-FSS
공식 코드Simpler is Better: Few-shot Semantic Segmentation with Classifier Weight Transformer
https://github.com/zwzheng98/qclnet
공식 코드Quaternion-valued Correlation Learning for Few-Shot Semantic Segmentation
https://github.com/AhmetSencan/MaskSplit-Self-supervised-Meta-learning-for-Few-shot-Semantic-Segmentation
MaskSplit: Self-supervised Meta-learning for Few-shot Semantic Segmentation
https://github.com/Bingolby/medical_few_shot_segmentation
Few-Shot Segmentation Without Meta-Learning: A Good Transductive Inference Is All You Need?
https://github.com/CSCYQJ/LOCATION-SENSITIVE-LOCAL-PROTOTYPE-NETWORK
PANet: Few-Shot Image Semantic Segmentation with Prototype Alignment
https://github.com/IBM/BCM
https://github.com/Meidianwen/few_shot_segmentation
Adaptive Prototype Learning and Allocation for Few-Shot Segmentation
https://github.com/RogerQi/pascal-5i
PANet: Few-Shot Image Semantic Segmentation with Prototype Alignment
https://github.com/SunghwanHong/Cost-Aggregation-transformers
https://github.com/YanFangCS/CyCTR-Pytorch
https://github.com/aldipiroli/semantic_spray_dataset
Label-Efficient Semantic Segmentation of LiDAR Point Clouds in Adverse Weather Conditions
https://github.com/cheng-01037/ssl_few_shot_med_img_seg
Self-Supervision with Superpixels: Training Few-shot Medical Image Segmentation without Annotation
https://github.com/dvlab-research/pfenet
Prior Guided Feature Enrichment Network for Few-Shot Segmentation
https://github.com/icoz69/CaNet
https://github.com/lsa1997/POP
https://github.com/pwc-1/Paper-10/tree/main/seggpt
https://github.com/rayat137/VisualPromptGFSS
Visual Prompting for Generalized Few-shot Segmentation: A Multi-scale Approach
https://github.com/sourachakra/densesubgraphsaliency
A dense subgraph based algorithm for compact salient image region detection
https://github.com/voxelmorph/voxelmorph
Unsupervised Deep Learning for Bayesian Brain MRI Segmentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.