awesome-multi-label-image-recognition

[Order-Free RNN] Order-Free RNN with Visual Attention for Multi-Label Classification

[SRN] Learning Spatial Regularization with Image-level Supervisions for Multi-label Image Classification

[CNN-RNN] CNN-RNN: A Unified Framework for Multi-label Image Classification

[WILDCAT] WILDCAT: Weakly Supervised Learning of Deep ConvNets for Image Classification, Pointwise Localization and Segmentation

[RDAR] Multi-label Image Recognition by Recurrently Discovering Attentional Regions

[MsDPD] Multi-scale and Discriminative Part Detectors Based Features for Multi-label Image Classification

[KSSNet] Multi-Label Classification with Label Graph Superimposing

[MS-CMA] Cross-Modality Attention with Semantic Graph Embedding for Multi-Label Classification

[SGTN] Privacy-Preserving Visual Content Tagging using Graph Transformer Networks

[AdaHGNN] AdaHGNN: Adaptive Hypergraph Neural Networks for Multi-Label Image Classification

[PLA] Orderless_Recurrent_Models_for_Multi-Label_Classification

[ADD-GCN] Attention-Driven Dynamic Graph Convolutional Network for Multi-Label Image Recognition

Semantic-Aware Representation Blending for Multi-Label Image Recognition with Partial Labels

Interactive Multi-Label CNN Learning with Partial Labels

Learning a Deep ConvNet for Multi-label Classification with Partial Labels

Exploiting weakly supervised visual patterns to learn from partial annotations

[DSDL] Deep Semantic Dictionary Learning for Multi-label Image Classification

[MGTN] Modular Graph Transformer Networks for Multi-Label Image Classification

[M3TR] M3TR: Multi-modal Multi-label Recognition with Transformer

MlTr: Multi-label Classification with Transformer

Query2Label: A Simple Transformer Way to Multi-Label Classification

[C-Trans] General Multi-label Image Classification with Transformers

Inferring Prototypes for Multi-Label Few-Shot Image Classification with Word Vector Guided Attention

Meta-Learning for Multi-Label Few-Shot Classification

Multi-label Learning from Noisy Labels with Non-linear Feature Transformation

Weakly Supervised Image Classification through Noise Regularization

Learning From Noisy Large-Scale Datasets With Minimal Supervision

Confidence-basedWeighted Loss for Multi-label Classification with Missing Labels

A Shared Multi-Attention Framework for Multi-Label Zero-Shot Learning

Multi-Label Zero-Shot Learning with Structured Knowledge Graphs

Fast Zero-Shot Image Tagging

Semantic Diversity Learning for Zero-Shot Multi-label Classification

[ML-GCN] Multi-Label Image Recognition with Graph Convolutional Networks

[VAC] Visual Attention Consistency under Image Transforms for Multi-Label Image Classification

[SSGRL] Learning Semantic-Specific Graph Representation for Multi-Label Image Recognition

Multi-Label Image Recognition with Joint Class-Aware Map Disentangling and Label Correlation Embedding

Multi-label Image Classification via Feature/Label Co-Projection