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 551–600 of 6661 papers

TitleStatusHype
Bridging the Gap: A Unified Video Comprehension Framework for Moment Retrieval and Highlight DetectionCode1
Anatomy-Constrained Contrastive Learning for Synthetic Segmentation without Ground-truthCode1
Contrastive Learning of Generalized Game RepresentationsCode1
Contrastive Learning of Musical RepresentationsCode1
From t-SNE to UMAP with contrastive learningCode1
Contrastive Meta Learning with Behavior Multiplicity for RecommendationCode1
Contrastive Trajectory Similarity Learning with Dual-Feature AttentionCode1
Cross-Modal Contrastive Learning of Representations for Navigation using Lightweight, Low-Cost Millimeter Wave Radar for Adverse Environmental ConditionsCode1
Contrastive Learning from Spatio-Temporal Mixed Skeleton Sequences for Self-Supervised Skeleton-Based Action RecognitionCode1
Contrastive Learning Improves Model Robustness Under Label NoiseCode1
Contrastive Learning for Weakly Supervised Phrase GroundingCode1
Anatomical Invariance Modeling and Semantic Alignment for Self-supervised Learning in 3D Medical Image AnalysisCode1
Contrastive Learning from Extremely Augmented Skeleton Sequences for Self-supervised Action RecognitionCode1
Contrastive Learning Inverts the Data Generating ProcessCode1
Anatomical Foundation Models for Brain MRIsCode1
Contrastive Learning for Unpaired Image-to-Image TranslationCode1
Bootstrapping Interactive Image-Text Alignment for Remote Sensing Image CaptioningCode1
Large-Scale Representation Learning on Graphs via BootstrappingCode1
Contrastive Learning for Sports Video: Unsupervised Player ClassificationCode1
Contrastive Learning for Unsupervised Domain Adaptation of Time SeriesCode1
Contrastive Learning Is Spectral Clustering On Similarity GraphCode1
Contrastive Learning for Neural Topic ModelCode1
Contrastive Learning for Prompt-Based Few-Shot Language LearnersCode1
DiffAug: Enhance Unsupervised Contrastive Learning with Domain-Knowledge-Free Diffusion-based Data AugmentationCode1
AdCo: Adversarial Contrast for Efficient Learning of Unsupervised Representations from Self-Trained Negative AdversariesCode1
Contrastive Learning for Many-to-many Multilingual Neural Machine TranslationCode1
Contrastive learning for regression in multi-site brain age predictionCode1
AD-CLIP: Adapting Domains in Prompt Space Using CLIPCode1
Contrastive Learning for Improving ASR Robustness in Spoken Language UnderstandingCode1
Contrastive Learning for Conversion Rate PredictionCode1
Bootstrapping meaning through listening: Unsupervised learning of spoken sentence embeddingsCode1
Contrastive Learning for Cross-Domain Open World RecognitionCode1
Contrastive Learning for Knowledge TracingCode1
Contrastive Learning for Representation Degeneration Problem in Sequential RecommendationCode1
Contrastive Learning and Mixture of Experts Enables Precise Vector EmbeddingsCode1
Adaptive Supervised PatchNCE Loss for Learning H&E-to-IHC Stain Translation with Inconsistent Groundtruth Image PairsCode1
Contrastive Learning-Based Audio to Lyrics Alignment for Multiple LanguagesCode1
Contrastive Laplacian EigenmapsCode1
Contrastive Label Disambiguation for Partial Label LearningCode1
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 Denoising Score for Text-guided Latent Diffusion Image EditingCode1
Contrastive Embeddings for Neural ArchitecturesCode1
Contrastive Deep Nonnegative Matrix Factorization for Community DetectionCode1
Adaptive Soft Contrastive LearningCode1
Contrastive Deep SupervisionCode1
Contrastive Fine-grained Class Clustering via Generative Adversarial NetworksCode1
A Multi-Task Semantic Decomposition Framework with Task-specific Pre-training for Few-Shot NERCode1
Contrastive Identity-Aware Learning for Multi-Agent Value DecompositionCode1
Best of Both Worlds: Multimodal Contrastive Learning with Tabular and Imaging DataCode1
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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