Papers Multi-label Image Recognition with Partial Labels
“Multi-label Image Recognition with Partial Labels” 태그가 달린 논문 12편 · 필터 해제
Learning Semantic-Aware Threshold for Multi-Label Image Recognition with Partial Labels
Multi-label image recognition with partial labels (MLR-PL) is designed to train models using a mix of known and unknown labels. Traditional methods rely on semantic or feature correlations to create pseudo-labels for uni…
Multi-label Image Recognition with Partial LabelsSaliency Regularization for Self-Training with Partial Annotations
Partially annotated images are easy to obtain in multi-label classification. However, unknown labels in partially annotated images exacerbate the positive-negative imbalance inherent in multi-label classification, wh…
Multi-Label ClassificationMUlTI-LABEL-ClASSIFICATIONMulti-label Image Recognition with Partial LabelsTexts as Images in Prompt Tuning for Multi-Label Image Recognition
Prompt tuning has been employed as an efficient way to adapt large vision-language pre-trained models (e.g. CLIP) to various downstream tasks in data-limited or label-limited settings. Nonetheless, visual data (e.g., ima…
Contrastive LearningMulti-Label Image RecognitionMulti-label Image Recognition with Partial LabelsDualCoOp: Fast Adaptation to Multi-Label Recognition with Limited Annotations
Solving multi-label recognition (MLR) for images in the low-label regime is a challenging task with many real-world applications. Recent work learns an alignment between textual and visual spaces to compensate for insuff…
Multi-label Image Recognition with Partial LabelsDual-Perspective Semantic-Aware Representation Blending for Multi-Label Image Recognition with Partial Labels
Despite achieving impressive progress, current multi-label image recognition (MLR) algorithms heavily depend on large-scale datasets with complete labels, making collecting large-scale datasets extremely time-consuming a…
image-classificationImage ClassificationMulti-Label Image RecognitionMulti-label Image Recognition with Partial LabelsHeterogeneous Semantic Transfer for Multi-label Recognition with Partial Labels
Multi-label image recognition with partial labels (MLR-PL), in which some labels are known while others are unknown for each image, may greatly reduce the cost of annotation and thus facilitate large-scale MLR. We find t…
Multi-Label Image RecognitionMulti-label Image Recognition with Partial LabelsSemantic-Aware Representation Blending for Multi-Label Image Recognition with Partial Labels
Training the multi-label image recognition models with partial labels, in which merely some labels are known while others are unknown for each image, is a considerably challenging and practical task. To address this task…
Multi-Label Image RecognitionMulti-label Image Recognition with Partial LabelsStructured Semantic Transfer for Multi-Label Recognition with Partial Labels
Multi-label image recognition is a fundamental yet practical task because real-world images inherently possess multiple semantic labels. However, it is difficult to collect large-scale multi-label annotations due to the …
Multi-Label Image RecognitionMulti-label Image Recognition with Partial LabelsLearning Graph Convolutional Networks for Multi-Label Recognition and Applications
The task of multi-label image recognition is to predict a set of object labels that present in an image. As objects normally co-occur in an image, it is desirable to model label dependencies to improve recognition perfor…
Multi-Label ClassificationMUlTI-LABEL-ClASSIFICATIONMulti-Label Image RecognitionMulti-label Image Recognition with Partial LabelsKnowledge-Guided Multi-Label Few-Shot Learning for General Image Recognition
Recognizing multiple labels of an image is a practical yet challenging task, and remarkable progress has been achieved by searching for semantic regions and exploiting label dependencies. However, current works utilize R…
Few-Shot LearningMulti-Label Image RecognitionMulti-label Image Recognition with Partial LabelsLearning Semantic-Specific Graph Representation for Multi-Label Image Recognition
Recognizing multiple labels of images is a practical and challenging task, and significant progress has been made by searching semantic-aware regions and modeling label dependency. However, current methods cannot locate …
Graph Representation LearningMulti-Label ClassificationMulti-Label Image RecognitionMulti-label Image Recognition with Partial Labels+1Learning a Deep ConvNet for Multi-label Classification with Partial Labels
Deep ConvNets have shown great performance for single-label image classification (e.g. ImageNet), but it is necessary to move beyond the single-label classification task because pictures of everyday life are inherently m…
ClassificationGeneral Classificationimage-classificationImage Classification+4