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 501–550 of 6661 papers

TitleStatusHype
Dog nose print matching with dual global descriptor based on Contrastive LearningCode1
Domain Enhanced Arbitrary Image Style Transfer via Contrastive LearningCode1
Aligning Text to Image in Diffusion Models is Easier Than You ThinkCode1
A Unified Arbitrary Style Transfer Framework via Adaptive Contrastive LearningCode1
AASAE: Augmentation-Augmented Stochastic AutoencodersCode1
Bridge to Target Domain by Prototypical Contrastive Learning and Label Confusion: Re-explore Zero-Shot Learning for Slot FillingCode1
BIOSCAN-5M: A Multimodal Dataset for Insect BiodiversityCode1
Biomedical Entity Linking with Contrastive Context MatchingCode1
DRIM: Learning Disentangled Representations from Incomplete Multimodal Healthcare DataCode1
Driver Anomaly Detection: A Dataset and Contrastive Learning ApproachCode1
Contrastive Learning for Neural Topic ModelCode1
Contrastive Learning for Sports Video: Unsupervised Player ClassificationCode1
Contrastive Learning from Spatio-Temporal Mixed Skeleton Sequences for Self-Supervised Skeleton-Based Action RecognitionCode1
Contrastive Learning for Cross-Domain Open World RecognitionCode1
An Interactive Multi-modal Query Answering System with Retrieval-Augmented Large Language ModelsCode1
Contrastive Learning for Improving ASR Robustness in Spoken Language UnderstandingCode1
Contrastive Learning for Compact Single Image DehazingCode1
Contrastive Learning for Cold-Start RecommendationCode1
Contrastive Learning for Conversion Rate PredictionCode1
Contrastive Learning for Knowledge TracingCode1
Contrastive Learning and Mixture of Experts Enables Precise Vector EmbeddingsCode1
Advancing 3D Medical Image Analysis with Variable Dimension Transform based Supervised 3D Pre-trainingCode1
Contrastive Learning-Based Audio to Lyrics Alignment for Multiple LanguagesCode1
CLIBD: Bridging Vision and Genomics for Biodiversity Monitoring at ScaleCode1
3D-Aware Neural Body Fitting for Occlusion Robust 3D Human Pose EstimationCode1
Replication: Contrastive Learning and Data Augmentation in Traffic Classification Using a Flowpic Input RepresentationCode1
A Unified Generative Framework for Realistic Lidar Simulation in Autonomous Driving SystemsCode1
Contrastive Learning for Many-to-many Multilingual Neural Machine TranslationCode1
Contrastive Learning Improves Model Robustness Under Label NoiseCode1
Contrastive Fine-grained Class Clustering via Generative Adversarial NetworksCode1
Contrastive Embeddings for Neural ArchitecturesCode1
Contrastive Grouping with Transformer for Referring Image SegmentationCode1
Contrastive Deep SupervisionCode1
Contrastive Deep Nonnegative Matrix Factorization for Community DetectionCode1
Contrastive Denoising Score for Text-guided Latent Diffusion Image EditingCode1
Contrastive Identity-Aware Learning for Multi-Agent Value DecompositionCode1
Contrastive Collaborative Filtering for Cold-Start Item RecommendationCode1
Contrastive Code Representation LearningCode1
Contrastive Continual Learning with Importance Sampling and Prototype-Instance Relation DistillationCode1
An Empirical Study on Disentanglement of Negative-free Contrastive LearningCode1
BigVideo: A Large-scale Video Subtitle Translation Dataset for Multimodal Machine TranslationCode1
Contrastive ClusteringCode1
Contrastive Cross-domain Recommendation in MatchingCode1
Contrastive Label Disambiguation for Partial Label LearningCode1
An Efficient Self-Supervised Cross-View Training For Sentence EmbeddingCode1
Contrasting Intra-Modal and Ranking Cross-Modal Hard Negatives to Enhance Visio-Linguistic Compositional UnderstandingCode1
Contrasting with Symile: Simple Model-Agnostic Representation Learning for Unlimited ModalitiesCode1
AD-L-JEPA: Self-Supervised Spatial World Models with Joint Embedding Predictive Architecture for Autonomous Driving with LiDAR DataCode1
Boosting Contrastive Self-Supervised Learning with False Negative CancellationCode1
BirdSAT: Cross-View Contrastive Masked Autoencoders for Bird Species Classification and MappingCode1
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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