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LLVIP
LLVIP: A Visible-infrared Paired Dataset for Low-light VisionMeta-SelfLearning
Meta Self-learning for Multi-Source Domain Adaptation: A BenchmarkBCI
BCI: Breast Cancer Immunohistochemical Image Generation through Pyramid Pix2pixHHCL-ReID
Hard-sample Guided Hybrid Contrast Learning for Unsupervised Person Re-IdentificationCAC-UNet-DigestPath2019
1st to MICCAI DigestPath2019 challenge (https://digestpath2019.grand-challenge.org/Home/) on colonoscopy tissue segmentation and classification task. (MICCAI 2019) https://teacher.bupt.edu.cn/zhuchuang/en/index.htmIAST-ECCV2020
IAST: Instance Adaptive Self-training for Unsupervised Domain Adaptation (ECCV 2020) https://teacher.bupt.edu.cn/zhuchuang/en/index.htmBALNMP
Predicting Axillary Lymph Node Metastasis in Early Breast Cancer Using Deep Learning on Primary Tumor Biopsy Slides, BCNB DatasetPGDF
Sample Prior Guided Robust Model Learning to Suppress Noisy LabelsHIAST
This is the official implementation of "Hard-aware Instance Adaptive Self-training for Unsupervised Cross-domain Semantic Segmentation".Thyroid-Cytopathological-Diagnosis-with-AMIL_MSFF
Attention Based Multi-Instance Thyroid Cytopathological Diagnosis with Multi-Scale Feature FusionTCVC
Code of paper "Temporal Consistent Automatic Video Colorization via Semantic Correspondence"Glomeruli-Instance-Segmentation
bupt-ai-cz
The introduction and news of CVSM Group.Label-Noise-Robust-Training
Noise Robust Learning with Hard Example Aware for Pathological Image classificationThyroid-Nodule-Ultrasound-Image-Classification
Thyroid Nodule Ultrasound Image Classification Through Hybrid Feature Cropping NetworkMPFN
Ischemic Stroke Lesion Segmentation Using Multi-Plane Information FusionProML
code for "Semi-supervised Domain Adaptation via Prototype-based Multi-level Learning"ANRN
IAST-CAC-UNet-LLCNN-BreastCancerCNN-ImageRetrieval_DF_CDVS-Highly_Efficient_Follicular_Segmentation
Codes and Data for CVSM Group: 1. IAST: Instance Adaptive Self-training for Unsupervised Domain Adaptation (ECCV 2020); 2.WUDA
WUDATCNL
SMAF
code for paper “A SELF-TRAINING FRAMEWORK BASED ON MULTI-SCALE ATTENTION FUSION FOR WEAKLY SUPERVISED SEMANTIC SEGMENTATION”Love Open Source and this site? Check out how you can help us