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 1551–1600 of 6661 papers

TitleStatusHype
Composite Sketch+Text Queries for Retrieving Objects with Elusive Names and Complex InteractionsCode1
CSLP-AE: A Contrastive Split-Latent Permutation Autoencoder Framework for Zero-Shot Electroencephalography Signal ConversionCode1
Learning Dialogue Representations from Consecutive UtterancesCode1
CoT-BERT: Enhancing Unsupervised Sentence Representation through Chain-of-ThoughtCode1
Contrastive Domain Adaptation for Time-Series via Temporal MixupCode1
Graph Contrastive Invariant Learning from the Causal PerspectiveCode1
Composed Image Retrieval using Contrastive Learning and Task-oriented CLIP-based FeaturesCode1
Graph-Aware Contrasting for Multivariate Time-Series ClassificationCode1
Cross-Patch Dense Contrastive Learning for Semi-Supervised Segmentation of Cellular Nuclei in Histopathologic ImagesCode1
Graph Contrastive Learning with Adaptive AugmentationCode1
Counterfactual contrastive learning: robust representations via causal image synthesisCode1
Graph Contrastive Learning Meets Graph Meta Learning: A Unified Method for Few-shot Node TasksCode1
Graph Contrastive Learning with AugmentationsCode1
Graph Contrastive Learning with Cohesive Subgraph AwarenessCode1
Graph Enhanced Contrastive Learning for Radiology Findings SummarizationCode1
Cross-Silo Prototypical Calibration for Federated Learning with Non-IID DataCode1
CP2: Copy-Paste Contrastive Pretraining for Semantic SegmentationCode1
CDPAM: Contrastive learning for perceptual audio similarityCode1
Adversarial Self-Supervised Contrastive LearningCode1
Enhancing Text-based Knowledge Graph Completion with Zero-Shot Large Language Models: A Focus on Semantic EnhancementCode1
Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate ReductionCode1
Revisiting Graph Contrastive Learning from the Perspective of Graph SpectrumCode1
Graph Self-supervised Learning with Accurate Discrepancy LearningCode1
Revisiting Multimodal Representation in Contrastive Learning: From Patch and Token Embeddings to Finite Discrete TokensCode1
Learning from Missing Relations: Contrastive Learning with Commonsense Knowledge Graphs for Commonsense InferenceCode1
3D Interaction Geometric Pre-training for Molecular Relational LearningCode1
cRedAnno+: Annotation Exploitation in Self-Explanatory Lung Nodule DiagnosisCode1
CRIS: CLIP-Driven Referring Image SegmentationCode1
Learning Robust Deep Visual Representations from EEG Brain RecordingsCode1
R-MAE: Regions Meet Masked AutoencodersCode1
Artistic Style Transfer with Internal-external Learning and Contrastive LearningCode1
CROMA: Remote Sensing Representations with Contrastive Radar-Optical Masked AutoencodersCode1
COMPLETER: Incomplete Multi-view Clustering via Contrastive PredictionCode1
G-SimCLR: Self-Supervised Contrastive Learning with Guided Projection via Pseudo LabellingCode1
ArtNeRF: A Stylized Neural Field for 3D-Aware Cartoonized Face SynthesisCode1
Cross-Architecture Self-supervised Video Representation LearningCode1
Adversarial Training of Self-supervised Monocular Depth Estimation against Physical-World AttacksCode1
Guarding Barlow Twins Against Overfitting with Mixed SamplesCode1
CrossCBR: Cross-view Contrastive Learning for Bundle RecommendationCode1
Guided Point Contrastive Learning for Semi-supervised Point Cloud Semantic SegmentationCode1
ASCON: Anatomy-aware Supervised Contrastive Learning Framework for Low-dose CT DenoisingCode1
RODD: A Self-Supervised Approach for Robust Out-of-Distribution DetectionCode1
Learning Audio-Visual Source Localization via False Negative Aware Contrastive LearningCode1
Hallucination Augmented Contrastive Learning for Multimodal Large Language ModelCode1
Cross-Domain Graph Anomaly Detection via Anomaly-aware Contrastive AlignmentCode1
Cross-Domain Sentiment Classification with Contrastive Learning and Mutual Information MaximizationCode1
Cross-Domain Sentiment Classification with In-Domain Contrastive LearningCode1
Hard Negative Mixing for Contrastive LearningCode1
Cross-level Contrastive Learning and Consistency Constraint for Semi-supervised Medical Image SegmentationCode1
Learning Better Contrastive View from Radiologist's GazeCode1
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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