Papers • Tutorials • Talks • Blogs • Datasets & Benchmarks
Multi-label Image Recognition
Pub. | Title | Links |
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TPAMI | [KGGR] Knowledge-Guided Multi-Label Few-Shot Learning for General Image Recognition | |
TIP | [SST] SST: Spatial and Semantic Transformers for Multi-label Image Recognition | |
TNNLS | [FDDS] Multilabel Convolutional Network With Feature Denoising and Details Supplement | |
arxiv | [GATN] Graph Attention Transformer Network for Multi-Label Image Classification |
Pub. | Title | Links |
---|---|---|
TPAMI | [P-GCN] Learning Graph Convolutional Networks for Multi-Label Recognition and Applications | |
TIP | [MCAR] Learning to Discover Multi-Class Attentional Regions for Multi-Label Image Recognition | PDF/Code |
CVPR | [C-Trans] General Multi-label Image Classification with Transformers | PDF/Code |
ICCV | [TDRG] Transformer-based Dual Relation Graph for Multi-label Image Recognition | PDF/Code |
ICCV | [ASL] Asymmetric Loss For Multi-Label Classification | PDF/Code |
ICCV | [CSRA] Residual Attention: A Simple but Effective Method for Multi-Label Recognition | PDF/Code |
ICCV | [TkML-AP] TkML-AP: Adversarial Attacks to Top-k Multi-Label Learning | |
AAAI | [DSDL] Deep Semantic Dictionary Learning for Multi-label Image Classification | PDF/Code |
AAAI | [MGTN] Modular Graph Transformer Networks for Multi-Label Image Classification | PDF/Code |
IJCAI | [GM-MLIC] GM-MLIC: Graph Matching based Multi-Label Image Classification | |
ACM MM | [M3TR] M3TR: Multi-modal Multi-label Recognition with Transformer | PDF/Code |
arxiv | MlTr: Multi-label Classification with Transformer | PDF/Code |
arxiv | Query2Label: A Simple Transformer Way to Multi-Label Classification | PDF/Code |
arxiv | Multi-layered Semantic Representation Network for Multi-label Image Classification | |
arxiv | Contrast Learning Visual Attention for Multi Label Classification | |
arxiv | Learning Discriminative Representations for Multi-Label Image Recognition | |
arxiv | Fine-Grained AutoAugmentation for Multi-Label Classification |
Pub. | Title | Links |
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TMM | [DER] Disentangling, Embedding and Ranking Label Cues for Multi-Label Image Recognition | |
TMM | [TS-GCN] Joint Input and Output Space Learning for Multi-Label Image Classification | |
CVPR | [PLA] Orderless_Recurrent_Models_for_Multi-Label_Classification | PDF/Code |
CVPR | Don’t Judge an Object by Its Context: Learning to Overcome Contextual Bias | PDF/Code |
ECCV | [ADD-GCN] Attention-Driven Dynamic Graph Convolutional Network for Multi-Label Image Recognition | PDF/Code |
AAAI | [KSSNet] Multi-Label Classification with Label Graph Superimposing | PDF/Code |
AAAI | Cross-Modality Attention with Semantic Graph Embedding for Multi-Label Classification | |
ACM MM | [SGTN] Privacy-Preserving Visual Content Tagging using Graph Transformer Networks | PDF/Code |
ACM MM | [AdaHGNN] AdaHGNN: Adaptive Hypergraph Neural Networks for Multi-Label Image Classification | |
arxiv | [IA-GCN] Instance-Aware Graph Convolutional Network for Multi-Label Classification |
Pub. | Title | Links |
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CVPR | [ML-GCN] Multi-Label Image Recognition with Graph Convolutional Networks | PDF/Code |
CVPR | [VAC] Visual Attention Consistency under Image Transforms for Multi-Label Image Classification | PDF/Code |
ICCV | [SSGRL] Learning Semantic-Specific Graph Representation for Multi-Label Image Recognition | PDF/Code |
Pub. | Title | Links |
---|---|---|
TPAMI'15 | [HCP] HCP: A Flexible CNN Framework for Multi-Label Image Classification | |
AAAI'18 | [Order-Free RNN] Order-Free RNN with Visual Attention for Multi-Label Classification | |
AAAI'19 | Recurrent Attentional Reinforcement Learning for Multi-label Image Recognition | |
IJCAI'18 | [MsDPD] Multi-scale and Discriminative Part Detectors Based Features for Multi-label Image Classification | |
ICCV'17 | [WILDCAT] WILDCAT: Weakly Supervised Learning of Deep ConvNets for Image Classification, Pointwise Localization and Segmentation | PDF/Code |
ICCV'17 | [RDAR] Multi-label Image Recognition by Recurrently Discovering Attentional Regions | PDF/Code |
CVPR'17 | [SRN] Learning Spatial Regularization with Image-level Supervisions for Multi-label Image Classification | PDF/Code |
CVPR'16 | [CNN-RNN] CNN-RNN: A Unified Framework for Multi-label Image Classification | PDF/Code |
Few/Zero-shot Multi-label Image Recognition
Pub. | Title | Links |
---|---|---|
TPAMI'20 | [KGGR] Knowledge-Guided Multi-Label Few-Shot Learning for General Image Recognition | |
TIP'20 | Deep Ranking for Image Zero-Shot Multi-Label Classification | |
AAAI'22 | Inferring Prototypes for Multi-Label Few-Shot Image Classification with Word Vector Guided Attention | |
ICCV'21 | [BiAM] Discriminative Region-based Multi-Label Zero-Shot Learning | PDF/Code |
ICCV'21 | Semantic Diversity Learning for Zero-Shot Multi-label Classification | PDF/Code |
ICCV'21 | Interaction Compass: Multi-Label Zero-Shot Learning of Human-Object Interactions via Spatial Relations | |
CVPR'20 | A Shared Multi-Attention Framework for Multi-Label Zero-Shot Learning | |
CVPR'18 | Multi-Label Zero-Shot Learning with Structured Knowledge Graphs | PDF/Code |
CVPR'16 | Fast Zero-Shot Image Tagging | PDF/Code |
arxiv | Multi-Label Learning from Single Positive Labels | |
arxiv | Towards Unbiased Multi-label Zero-Shot Learning with Pyramid and Semantic Attention |
Multi-label Image Recognition with Missing Labels
Pub. | Title | Links |
---|---|---|
TPAMI'21 | [P-GCN] Learning Graph Convolutional Networks for Multi-Label Recognition and Applications | |
AAAI'22 | [SARB] Semantic-Aware Representation Blending for Multi-Label Image Recognition with Partial Labels | PDF/Code |
AAAI'22 | [SST] Structured Semantic Transfer for Multi-Label Recognition with Partial Labels | PDF/Code |
CVPR'21 | Multi-Label Learning from Single Positive Labels | |
CVPR'20 | Interactive Multi-Label CNN Learning with Partial Labels | |
NeurIPS'20 | Exploiting weakly supervised visual patterns to learn from partial annotations | |
CVPR'19 | Learning a Deep ConvNet for Multi-label Classification with Partial Labels | |
arxiv | Spatial Consistency Loss for Training Multi-Label Classifiers from Single-Label Annotations | |
arxiv | Simple and Robust Loss Design for Multi-Label Learning with Missing Labels | |
arxiv | [ATAM] Rethinking Crowdsourcing Annotation: Partial Annotation with Salient Labels for Multi-Label Image Classification | |
arxiv | Multi-label Classification with Partial Annotations using Class-aware Selective Loss | PDF/Code |
arxiv | Acknowledging the Unknown for Multi-label Learning with Single Positive Labels |
Multi-label Image Recognition with Nosiy Labels
Pub. | Title | Links |
---|---|---|
CVPR'19 | Weakly Supervised Image Classification through Noise Regularization | |
CVPR'17 | Learning From Noisy Large-Scale Datasets With Minimal Supervision |
Multi-label Image Recognition with Long-tailed Labels
Pub. | Title | Links |
---|---|---|
CVPR'21 | Long-Tailed Multi-Label Visual Recognition by Collaborative Training on Uniform and Re-balanced Samplings | |
ECCV'20 | Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datasets | PDF/Code |
Tutorials published on 2021
Pub. | Title | Links |
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COCO2014
Methods | Input Size | Architecture | mAP | CP | CR | CF1 | OP | OR | OF1 |
---|---|---|---|---|---|---|---|---|---|
ML-GCN (CVPR'19) | (448, 448) | CNN-based | 83.0 | 85.1 | 72.0 | 78.0 | 85.8 | 75.4 | 80.3 |
P-GCN(TPAMI'21) | (448,448) | CNN-based | 83.2 | 84.9 | 72.7 | 78.3 | 85.0 | 76.4 | 80.5 |
MCAR(TIP'21) | (448,448) | CNN-based | 83.8 | 85.0 | 72.1 | 78.0 | 88.0 | 73.9 | 80.3 |
ADD-GCN (ECCV'20) | (448, 448) | CNN-based | 85.2 | 84.7 | 75.9 | 80.1 | 84.9 | 79.4 | 82.0 |
SSGRL (ICCV'19) | (576,576) | CNN-based | 83.8 | 89.9 | 68.5 | 76.8 | 91.3 | 70.8 | 79.7 |
KGGR (TPAMI'20) | (576, 576) | CNN-based | 84.3 | 85.6 | 72.7 | 78.6 | 87.1 | 75.6 | 80.9 |
MCAR(TIP'21) | (576,576) | CNN-based | 84.5 | 84.3 | 73.9 | 78.7 | 86.9 | 76.1 | 81.1 |
AdaHGNN(ACM MM'20) | (576,576) | CNN-based | 85.0 | - | - | 79.9 | - | - | 81.8 |
TDRG(ICCV21) | (448,448) | CNN-Transformer | 84.6 | 86.0 | 73.1 | 79.0 | 86.6 | 76.4 | 81.2 |
C-Tran(CVPR'21) | (576,576) | CNN-Transformer | 85.1 | 86.3 | 74.3 | 79.9 | 87.7 | 76.5 | 81.7 |
TDRG(ICCV'21) | (576,576) | CNN-Transformer | 86.0 | 87.0 | 74.7 | 80.4 | 87.5 | 77.9 | 82.4 |
Note: Only present the precision, recall, and F1-measure for all prediction scores.
Visual Genome 500
Methods | Input Size | Architecture | mAP | CP | CR | CF1 | OP | OR | OF1 |
---|---|---|---|---|---|---|---|---|---|
SSGRL (ICCV'19) | (576,576) | CNN-based | 36.6 | - | - | - | - | - | - |
KGGR (TPAMI'20) | (576, 576) | CNN-based | 37.4 | 48.7 | 12.1 | 19.4 | 78.6 | 17.1 | 28.1 |
AdaHGNN (ACM MM'20) | (576,576) | CNN-based | 38.2 | - | - | - | - | - | - |
C-Tran(CVPR'21) | (576,576) | CNN-Transformer | 38.4 | 49.8 | 27.2 | 35.2 | 66.9 | 39.2 | 49.5 |
Note: Only present the precision, recall, and F1-measure for all prediction scores.
VOC2007
Methods | Input Size | Architecture | mAP | CP | CR | CF1 | OP | OR | OF1 |
---|---|---|---|---|---|---|---|---|---|
ML-GCN (CVPR'19) | (448, 448) | CNN-based | 94.0 | - | - | - | - | - | - |
P-GCN(TPAMI'21) | (448,448) | CNN-based | 94.3 | - | - | - | - | - | - |
ADD-GCN (ECCV'20) | (448,448) | CNN-based | 96.0 | - | - | - | - | - | - |
SSGRL (ICCV'19) | (576,576) | CNN-based | 93.4 | - | - | - | - | - | - |
KGGR (TPAMI'20) | (576,576) | CNN-based | 93.6 | - | - | - | - | - | - |
MCAR(TIP'21) | (576,576) | CNN-based | 94.8 | - | - | - | - | - | - |
AdaHGNN(ACM MM'20) | (576,576) | CNN-based | 95.2 | - | - | - | - | - | - |
TDRG(ICCV21) | (448,448) | CNN-Transformer | 95.0 | - | - | - | - | - | - |
Note: Only present the precision, recall, and F1-measure for all prediction scores.