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Multi-Label Image Classification
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The Multi-Label Image Classification focuses on predicting labels for images in a multi-class classification problem where each image may belong to more than one class.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Multi-label Classification using Deep Multi-order Context-aware Kernel Networks
When the Small-Loss Trick is Not Enough: Multi-Label Image Classification with Noisy Labels Applied to CCTV Sewer Inspections
Category-Prompt Refined Feature Learning for Long-Tailed Multi-Label Image Classification
HSVLT: Hierarchical Scale-Aware Vision-Language Transformer for Multi-Label Image Classification
Multi-Label Plant Species Classification with Self-Supervised Vision Transformers
Resampled Datasets Are Not Enough: Mitigating Societal Bias Beyond Single Attributes
reBEN: Refined BigEarthNet Dataset for Remote Sensing Image Analysis
Combining Supervised Learning and Reinforcement Learning for Multi-Label Classification Tasks with Partial Labels
LADI v2: Multi-label Dataset and Classifiers for Low-Altitude Disaster Imagery
Free Performance Gain from Mixing Multiple Partially Labeled Samples in Multi-label Image Classification
Reproducibility Study of CDUL: CLIP-Driven Unsupervised Learning for Multi-Label Image Classification
ROCOv2: Radiology Objects in COntext Version 2, an Updated Multimodal Image Dataset
The impact of Compositionality in Zero-shot Multi-label action recognition for Object-based tasks
FolkTalent: Enhancing Classification and Tagging of Indian Folk Paintings
TAI++: Text as Image for Multi-Label Image Classification by Co-Learning Transferable Prompt
Multi-Label Continual Learning for the Medical Domain: A Novel Benchmark
Counterfactual Reasoning for Multi-Label Image Classification via Patching-Based Training
Estimating Physical Information Consistency of Channel Data Augmentation for Remote Sensing Images
Auxiliary Tasks Enhanced Dual-affinity Learning for Weakly Supervised Semantic Segmentation
NOAH: Learning Pairwise Object Category Attentions for Image Classification
Category-wise Fine-Tuning: Resisting Incorrect Pseudo-Labels in Multi-Label Image Classification with Partial Labels
ProbMCL: Simple Probabilistic Contrastive Learning for Multi-label Visual Classification
MS-Twins: Multi-Scale Deep Self-Attention Networks for Medical Image Segmentation
Language-Guided Transformer for Federated Multi-Label Classification
Text as Image: Learning Transferable Adapter for Multi-Label Classification
SpliceMix: A Cross-scale and Semantic Blending Augmentation Strategy for Multi-label Image Classification
Federated Learning Across Decentralized and Unshared Archives for Remote Sensing Image Classification
Feature Guided Masked Autoencoder for Self-supervised Learning in Remote Sensing
Conditional Consistency Regularization for Semi-Supervised Multi-label Image Classification
CDUL: CLIP-Driven Unsupervised Learning for Multi-Label Image Classification
Semantic-Aware Dual Contrastive Learning for Multi-label Image Classification
PatchCT: Aligning Patch Set and Label Set with Conditional Transport for Multi-Label Image Classification
Pseudo Labels for Single Positive Multi-Label Learning
Semantic Embedded Deep Neural Network: A Generic Approach to Boost Multi-Label Image Classification Performance
Category Query Learning for Human-Object Interaction Classification
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