https://github.com/linzy0227/pdminet
공식 코드Prototype-Driven and Multi-Expert Integrated Multi-Modal MR Brain Tumor Image Segmentation
Papers with Code 아카이브
Image Segmentation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 1
- 평가표
- 13
- 보존된 평가 기록
- 34
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/liqiokkk/fctl
공식 코드https://github.com/lironui/MACU-Net
공식 코드MACU-Net for Semantic Segmentation of Fine-Resolution Remotely Sensed Images
https://github.com/lironui/U-Net-with-Multi-Scale-Skip-Connections-and-Asymmetric-Convolution-Blocks
공식 코드MACU-Net for Semantic Segmentation of Fine-Resolution Remotely Sensed Images
https://github.com/lironui/aeroreformer
공식 코드AeroReformer: Aerial Referring Transformer for UAV-based Referring Image Segmentation
https://github.com/lisatwyw/smrvis
공식 코드SMRVIS: Point cloud extraction from 3-D ultrasound for non-destructive testing
https://github.com/littleaich/deepglobe2018
공식 코드Semantic Binary Segmentation using Convolutional Networks without Decoders
https://github.com/liu-yuxi/fedfms
공식 코드FedFMS: Exploring Federated Foundation Models for Medical Image Segmentation
https://github.com/liuhaozm/double-well-net
공식 코드https://github.com/liuquande/FedDG-ELCFS
공식 코드https://github.com/liutingwed/sam-not-perfect
공식 코드Segment Anything Is Not Always Perfect: An Investigation of SAM on Different Real-world Applications
https://github.com/liuweide01/Cross-Image-Region-Mining-with-Region-Prototypical-Network-for-Weakly-Supervised-Segmentation
공식 코드Cross-Image Region Mining with Region Prototypical Network for Weakly Supervised Segmentation
https://github.com/liuweide01/GQNet-Few-shot-segmentation
공식 코드Few-Shot Segmentation with Global and Local Contrastive Learning
https://github.com/liuxinyv/sazs
공식 코드https://github.com/liwentomng/point2mask
공식 코드Point2Mask: Point-supervised Panoptic Segmentation via Optimal Transport
https://github.com/liyunsheng13/BDL
공식 코드Bidirectional Learning for Domain Adaptation of Semantic Segmentation
https://github.com/ljollans/trunet
공식 코드Vision Transformers increase efficiency of 3D cardiac CT multi-label segmentation
https://github.com/llmir/fedicra
공식 코드https://github.com/llmir/fedlppa
공식 코드https://github.com/llmir/yolocurvseg
공식 코드YoloCurvSeg: You Only Label One Noisy Skeleton for Vessel-style Curvilinear Structure Segmentation
https://github.com/lloongx/sfda-cbmt
공식 코드Source-Free Domain Adaptive Fundus Image Segmentation with Class-Balanced Mean Teacher
https://github.com/lmiapc/fednnu-net
공식 코드FedFMS: Exploring Federated Foundation Models for Medical Image Segmentation
https://github.com/lofrienger/curri-afda
공식 코드Curriculum-Based Augmented Fourier Domain Adaptation for Robust Medical Image Segmentation
https://github.com/lofrienger/s2me
공식 코드https://github.com/logan-0623/pg-sam
공식 코드PG-SAM: Prior-Guided SAM with Medical for Multi-organ Segmentation
https://github.com/lolemacs/iem
공식 코드Information-Theoretic Segmentation by Inpainting Error Maximization
https://github.com/longmalongma/desa2va
공식 코드Decoupled Seg Tokens Make Stronger Reasoning Video Segmenter and Grounder
https://github.com/louey233/toward-mutual-information
공식 코드https://github.com/lsan2401/rmsin
공식 코드Rotated Multi-Scale Interaction Network for Referring Remote Sensing Image Segmentation
https://github.com/lseventeen/dias
공식 코드DIAS: A Dataset and Benchmark for Intracranial Artery Segmentation in DSA sequences
https://github.com/lseventeen/phtrans
공식 코드PHTrans: Parallelly Aggregating Global and Local Representations for Medical Image Segmentation
https://github.com/lswzjuer/NAS-WDAN
공식 코드MixSearch: Searching for Domain Generalized Medical Image Segmentation Architectures
https://github.com/ltu-machine-learning/analysis-of-deep-perceptual-loss-networks
공식 코드https://github.com/luancvieira/Textural-Heterogeneity-Measure
공식 코드Entropy-based measure of rock sample heterogeneity derived from micro-CT images
https://github.com/lucaballotta/vrem-fl
공식 코드VREM-FL: Mobility-Aware Computation-Scheduling Co-Design for Vehicular Federated Learning
https://github.com/lucasfidon/feta-inference
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.