SOTAVerified

Contrastive Learning

Contrastive Learning is a deep learning technique for unsupervised representation learning. The goal is to learn a representation of data such that similar instances are close together in the representation space, while dissimilar instances are far apart.

It has been shown to be effective in various computer vision and natural language processing tasks, including image retrieval, zero-shot learning, and cross-modal retrieval. In these tasks, the learned representations can be used as features for downstream tasks such as classification and clustering.

(Image credit: Schroff et al. 2015)

Papers

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Showing 1801–1850 of 6661 papers

TitleStatusHype
MoCo-CXR: MoCo Pretraining Improves Representation and Transferability of Chest X-ray ModelsCode1
Contrastive Learning with Hard Negative SamplesCode1
Unsupervised Representation Learning by InvariancePropagationCode1
Representation Learning for Sequence Data with Deep Autoencoding Predictive ComponentsCode1
Unsupervised Reference-Free Summary Quality Evaluation via Contrastive LearningCode1
Contrastive Learning of Medical Visual Representations from Paired Images and TextCode1
Hard Negative Mixing for Contrastive LearningCode1
Joint Contrastive Learning with Infinite PossibilitiesCode1
Driver Anomaly Detection: A Dataset and Contrastive Learning ApproachCode1
G-SimCLR: Self-Supervised Contrastive Learning with Guided Projection via Pseudo LabellingCode1
G-SimCLR : Self-Supervised Contrastive Learning with Guided Projection via Pseudo LabellingCode1
Label-Efficient Multi-Task Segmentation using Contrastive LearningCode1
Contrastive ClusteringCode1
DVG-Face: Dual Variational Generation for Heterogeneous Face RecognitionCode1
A Simple and Effective Self-Supervised Contrastive Learning Framework for Aspect DetectionCode1
MoPro: Webly Supervised Learning with Momentum PrototypesCode1
Domain-invariant Similarity Activation Map Contrastive Learning for Retrieval-based Long-term Visual LocalizationCode1
Group-wise Contrastive Learning for Neural Dialogue GenerationCode1
A Self-Supervised Gait Encoding Approach with Locality-Awareness for 3D Skeleton Based Person Re-IdentificationCode1
Unsupervised Feature Learning by Autoencoder and Prototypical Contrastive Learning for Hyperspectral ClassificationCode1
Active Contrastive Learning of Audio-Visual Video RepresentationsCode1
VLANet: Video-Language Alignment Network for Weakly-Supervised Video Moment RetrievalCode1
Self-supervised Video Representation Learning by Pace PredictionCode1
Spatiotemporal Contrastive Video Representation LearningCode1
Unsupervised Feature Learning by Cross-Level Instance-Group DiscriminationCode1
Deep Robust Clustering by Contrastive LearningCode1
Contrastive Variational Reinforcement Learning for Complex ObservationsCode1
Self-supervised Video Representation Learning Using Inter-intra Contrastive FrameworkCode1
Temporal Context Aggregation for Video Retrieval with Contrastive LearningCode1
SeCo: Exploring Sequence Supervision for Unsupervised Representation LearningCode1
Augmented Skeleton Based Contrastive Action Learning with Momentum LSTM for Unsupervised Action RecognitionCode1
Distilling Visual Priors from Self-Supervised LearningCode1
Contrastive Learning for Unpaired Image-to-Image TranslationCode1
Self-Supervised Contrastive Learning for Unsupervised Phoneme SegmentationCode1
3D Human Shape and Pose from a Single Low-Resolution Image with Self-Supervised LearningCode1
Hybrid Discriminative-Generative Training via Contrastive LearningCode1
CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted InstancesCode1
InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-TrainingCode1
InfoMax-GAN: Improved Adversarial Image Generation via Information Maximization and Contrastive LearningCode1
Contrastive Code Representation LearningCode1
Improving Weakly Supervised Visual Grounding by Contrastive Knowledge DistillationCode1
Data Augmenting Contrastive Learning of Speech Representations in the Time DomainCode1
Debiased Contrastive LearningCode1
Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text RetrievalCode1
Subject-Aware Contrastive Learning for BiosignalsCode1
Video Representation Learning with Visual Tempo ConsistencyCode1
On Equivariant and Invariant Learning of Object Landmark RepresentationsCode1
Joint Contrastive Learning for Unsupervised Domain AdaptationCode1
Supervision Accelerates Pre-training in Contrastive Semi-Supervised Learning of Visual RepresentationsCode1
Contrastive learning of global and local features for medical image segmentation with limited annotationsCode1
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All datasetsimagenet-1k10,000 People - Human Pose Recognition DataCIFAR-10STL-10

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ResNet50ImageNet Top-1 Accuracy73.6—Unverified
2ResNet50ImageNet Top-1 Accuracy73—Unverified
3ResNet50ImageNet Top-1 Accuracy71.1—Unverified
4ResNet50ImageNet Top-1 Accuracy69.3—Unverified
5ResNet50 (v2)ImageNet Top-1 Accuracy67.6—Unverified
6ResNet50 (v2)ImageNet Top-1 Accuracy63.8—Unverified
7ResNet50ImageNet Top-1 Accuracy63.6—Unverified
8ResNet50ImageNet Top-1 Accuracy61.5—Unverified
9ResNet50ImageNet Top-1 Accuracy61.5—Unverified
10ResNet50 (4×)ImageNet Top-1 Accuracy61.3—Unverified
#ModelMetricClaimedVerifiedStatus
110..5sec1—Unverified
#ModelMetricClaimedVerifiedStatus
1IPCL (ResNet18)Accuracy (Top-1)84.77—Unverified
#ModelMetricClaimedVerifiedStatus
1IPCL (ResNet18)Accuracy (Top-1)85.55—Unverified