https://github.com/xmed-lab/clip_surgery
공식 코드A Closer Look at the Explainability of Contrastive Language-Image Pre-training
Papers with Code 아카이브
Semantic Segmentation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 29
- 평가표
- 150
- 보존된 평가 기록
- 1,918
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/xmed-lab/cpr
공식 코드Context-Aware Pseudo-Label Refinement for Source-Free Domain Adaptive Fundus Image Segmentation
https://github.com/xmed-lab/dhc
공식 코드https://github.com/xmed-lab/epl_semidg
공식 코드Enhancing Pseudo Label Quality for Semi-Supervised Domain-Generalized Medical Image Segmentation
https://github.com/xmed-lab/mssg
공식 코드Morphology-inspired Unsupervised Gland Segmentation via Selective Semantic Grouping
https://github.com/xmed-lab/neurons
공식 코드https://github.com/xmed-lab/oeem
공식 코드Online Easy Example Mining for Weakly-supervised Gland Segmentation from Histology Images
https://github.com/xmed-lab/urn
공식 코드https://github.com/xmeimeimei/sgtc
공식 코드https://github.com/xmindflow/Laplacian-Former
공식 코드Laplacian-Former: Overcoming the Limitations of Vision Transformers in Local Texture Detection
https://github.com/xmindflow/cenet
공식 코드CENet: Context Enhancement Network for Medical Image Segmentation
https://github.com/xmindflow/deformableLKA
공식 코드Beyond Self-Attention: Deformable Large Kernel Attention for Medical Image Segmentation
https://github.com/xmindflow/fusenet
공식 코드FuseNet: Self-Supervised Dual-Path Network for Medical Image Segmentation
https://github.com/xmindflow/lhunet
공식 코드https://github.com/xmindflow/msa-2net
공식 코드MSA$^2$Net: Multi-scale Adaptive Attention-guided Network for Medical Image Segmentation
https://github.com/xmlyqing00/AFB-URR
공식 코드Video Object Segmentation with Adaptive Feature Bank and Uncertain-Region Refinement
https://github.com/xq141839/DCSAU-Net
공식 코드DCSAU-Net: A Deeper and More Compact Split-Attention U-Net for Medical Image Segmentation
https://github.com/xq141839/HRMedSeg
공식 코드https://github.com/xq141839/esp-medsam
공식 코드ESP-MedSAM: Efficient Self-Prompting SAM for Universal Domain-Generalized Medical Image Segmentation
https://github.com/xq141839/nusegdg
공식 코드https://github.com/xq141839/sppnet
공식 코드SPPNet: A Single-Point Prompt Network for Nuclei Image Segmentation
https://github.com/xrkong/skimba
공식 코드Skip Mamba Diffusion for Monocular 3D Semantic Scene Completion
https://github.com/xrt11/tumor-segmentation
공식 코드A Weakly Supervised and Globally Explainable Learning Framework for Brain Tumor Segmentation
https://github.com/xu-ji/IIC
공식 코드Invariant Information Clustering for Unsupervised Image Classification and Segmentation
https://github.com/xuanrui-work/wsssbyrec
공식 코드Semantic Segmentation from Image Labels by Reconstruction from Structured Decomposition
https://github.com/xuebinqin/DIS
공식 코드https://github.com/xuhu0529/sags
공식 코드SAGD: Boundary-Enhanced Segment Anything in 3D Gaussian via Gaussian Decomposition
https://github.com/xulabs/aitom
공식 코드https://github.com/xulianuwa/AuxSegNet
공식 코드Leveraging Auxiliary Tasks with Affinity Learning for Weakly Supervised Semantic Segmentation
https://github.com/xulianuwa/mctformer
공식 코드Multi-class Token Transformer for Weakly Supervised Semantic Segmentation
https://github.com/xuliu-cyber/rsunivlm
공식 코드https://github.com/xumengyaamy/p-cbls
공식 코드Confidence-Aware Paced-Curriculum Learning by Label Smoothing for Surgical Scene Understanding
https://github.com/xumengyaamy/synthetic_cat_sd
공식 코드Privacy-Preserving Synthetic Continual Semantic Segmentation for Robotic Surgery
https://github.com/xuqianren/semantic-guided-multi-mask-image-harmonization
공식 코드https://github.com/xushilin1/rap-sam
공식 코드https://github.com/xuxiaoxxxx/3DSS-VLG
공식 코드3D Weakly Supervised Semantic Segmentation with 2D Vision-Language Guidance
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.