https://github.com/kyanchen/rsrefseg2
공식 코드RSRefSeg 2: Decoupling Referring Remote Sensing Image Segmentation with Foundation Models
Papers with Code 아카이브
Image Segmentation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Image Segmentation is a computer vision task that involves dividing an image into multiple segments or regions, each of which corresponds to a different object or part of an object. The goal of image segmentation is to assign a unique label or category to each pixel in the image, so that pixels with similar attributes are grouped together.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/kytimmylai/dfuc2022
공식 코드https://github.com/kyyle2114/convolutional-adapter-for-segment-anything
공식 코드CAD: Memory Efficient Convolutional Adapter for Segment Anything
https://github.com/lab-smile/domino
공식 코드DOMINO: Domain-aware Model Calibration in Medical Image Segmentation
https://github.com/lab206/adaptiveclick
공식 코드AdaptiveClick: Clicks-aware Transformer with Adaptive Focal Loss for Interactive Image Segmentation
https://github.com/lambert-x/catenorm
공식 코드CateNorm: Categorical Normalization for Robust Medical Image Segmentation
https://github.com/lancasterli/refsam
공식 코드RefSAM: Efficiently Adapting Segmenting Anything Model for Referring Video Object Segmentation
https://github.com/lanqingl/scs
공식 코드Visual Prompt Selection for In-Context Learning Segmentation
https://github.com/lans1ng/pointsam
공식 코드PointSAM: Pointly-Supervised Segment Anything Model for Remote Sensing Images
https://github.com/lars76/segmentation_activations
공식 코드https://github.com/lartpang/ovcamo
공식 코드https://github.com/lartpang/zoomnet
공식 코드Zoom In and Out: A Mixed-scale Triplet Network for Camouflaged Object Detection
https://github.com/leaplabthu/deep-incubation
공식 코드Deep Incubation: Training Large Models by Divide-and-Conquering
https://github.com/leaplabthu/model-assembling
공식 코드Deep Incubation: Training Large Models by Divide-and-Conquering
https://github.com/leejieyu13/lidarcameradataset
공식 코드2D LiDAR and Camera Fusion Using Motion Cues for Indoor Layout Estimation
https://github.com/leesoon1984/cmmt-net
공식 코드Cross-head mutual Mean-Teaching for semi-supervised medical image segmentation
https://github.com/leiluk1/gaze-based-segmentation
공식 코드https://github.com/leipingjie/sam2video
공식 코드https://github.com/leipingjie/samshadow
공식 코드https://github.com/leongdong/bias-decomposition-networks
공식 코드Unsupervised Decomposition Networks for Bias Field Correction in MR Image
https://github.com/levayz/dinov2-based-self-supervised-learning
공식 코드DINOv2 based Self Supervised Learning For Few Shot Medical Image Segmentation
https://github.com/levayz/protosam
공식 코드ProtoSAM: One-Shot Medical Image Segmentation With Foundational Models
https://github.com/lhaof/asa
공식 코드https://github.com/lhaof/nnmamba
공식 코드https://github.com/lhaof/nudiff
공식 코드Diffusion-based Data Augmentation for Nuclei Image Segmentation
https://github.com/lhoyer/hrda
공식 코드https://github.com/liamchalcroft/mdunet
공식 코드Large-kernel Attention for Efficient and Robust Brain Lesion Segmentation
https://github.com/liamheng/non-iid_medical_image_segmentation
공식 코드Frequency-mixed Single-source Domain Generalization for Medical Image Segmentation
https://github.com/lich0031/AIDE
공식 코드Annotation-efficient deep learning for automatic medical image segmentation
https://github.com/lids-unicamp/rethinking-interactive-image-segmentation
공식 코드Rethinking Interactive Image Segmentation: Feature Space Annotation
https://github.com/lik1996/icmformer
공식 코드Interactive Image Segmentation with Cross-Modality Vision Transformers
https://github.com/liliu-avril/Awesome-Segment-Anything
공식 코드https://github.com/lilygoli/longitudinalCOVID
공식 코드Longitudinal Quantitative Assessment of COVID-19 Infection Progression from Chest CTs
https://github.com/lin-tianyu/stable-diffusion-seg
공식 코드Stable Diffusion Segmentation for Biomedical Images with Single-step Reverse Process
https://github.com/linchenq/transdeformer-mesh
공식 코드https://github.com/lingrayy/plpb
공식 코드Robust Source-Free Domain Adaptation for Fundus Image Segmentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.