Learning with coarse labels
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Benchmarks
Most implemented
Twofold Debiasing Enhances Fine-Grained Learning with Coarse Labels
Weakly supervised segmentation of intracranial aneurysms using a novel 3D focal modulation UNet
MaskCon: Masked Contrastive Learning for Coarse-Labelled Dataset
Fine-grained Angular Contrastive Learning with Coarse Labels
Weakly Supervised Representation Learning with Coarse Labels
Papers
Twofold Debiasing Enhances Fine-Grained Learning with Coarse Labels
The Coarse-to-Fine Few-Shot (C2FS) task is designed to train models using only coarse labels, then leverages a limited number of subclass samples to achieve fine-grained recognition capabilities. This task presents two m…
Learning with coarse labelsWeakly supervised segmentation of intracranial aneurysms using a novel 3D focal modulation UNet
Accurate identification and quantification of unruptured intracranial aneurysms (UIAs) is crucial for the risk assessment and treatment of this cerebrovascular disorder. Current 2D manual assessment on 3D magnetic resona…
Image SegmentationLearning with coarse labelsMedical Image SegmentationSegmentation+3MaskCon: Masked Contrastive Learning for Coarse-Labelled Dataset
Deep learning has achieved great success in recent years with the aid of advanced neural network structures and large-scale human-annotated datasets. However, it is often costly and difficult to accurately and efficientl…
Contrastive LearningLearning with coarse labelsFine-grained Angular Contrastive Learning with Coarse Labels
Few-shot learning methods offer pre-training techniques optimized for easier later adaptation of the model to new classes (unseen during training) using one or a few examples. This adaptivity to unseen classes is especia…
Contrastive LearningFew-Shot LearningLearning with coarse labelsGrafit: Learning fine-grained image representations with coarse labels
This paper tackles the problem of learning a finer representation than the one provided by training labels. This enables fine-grained category retrieval of images in a collection annotated with coarse labels only. Our ne…
Fine-Grained Image ClassificationImage ClassificationLearning with coarse labelsRetrieval+2Weakly Supervised Representation Learning with Coarse Labels
With the development of computational power and techniques for data collection, deep learning demonstrates a superior performance over most existing algorithms on visual benchmark data sets. Many efforts have been devote…
Deep LearningLearning with coarse labelsRepresentation Learning