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
Contrastive Denoising Score for Text-guided Latent Diffusion Image EditingCode1
Dog nose print matching with dual global descriptor based on Contrastive LearningCode1
Chaos is a Ladder: A New Theoretical Understanding of Contrastive Learning via Augmentation OverlapCode1
A Unified Arbitrary Style Transfer Framework via Adaptive Contrastive LearningCode1
AASAE: Augmentation-Augmented Stochastic AutoencodersCode1
Domain Knowledge-Informed Self-Supervised Representations for Workout Form AssessmentCode1
Contrastive Fine-grained Class Clustering via Generative Adversarial NetworksCode1
Chameleon: Adapting to Peer Images for Planting Durable Backdoors in Federated LearningCode1
Driver Anomaly Detection: A Dataset and Contrastive Learning ApproachCode1
Contrastive Embeddings for Neural ArchitecturesCode1
CIC: Contrastive Intrinsic Control for Unsupervised Skill DiscoveryCode1
cRedAnno+: Annotation Exploitation in Self-Explanatory Lung Nodule DiagnosisCode1
CrossCBR: Cross-view Contrastive Learning for Bundle RecommendationCode1
Certifiably Robust Graph Contrastive LearningCode1
An Interactive Multi-modal Query Answering System with Retrieval-Augmented Large Language ModelsCode1
Counterfactual contrastive learning: robust representations via causal image synthesisCode1
CoT-BERT: Enhancing Unsupervised Sentence Representation through Chain-of-ThoughtCode1
CETN: Contrast-enhanced Through Network for CTR PredictionCode1
Contrastive Domain Adaptation for Time-Series via Temporal MixupCode1
CP2: Copy-Paste Contrastive Pretraining for Semantic SegmentationCode1
CCL: Continual Contrastive Learning for LiDAR Place RecognitionCode1
Advancing 3D Medical Image Analysis with Variable Dimension Transform based Supervised 3D Pre-trainingCode1
CDPAM: Contrastive learning for perceptual audio similarityCode1
CoSQA: 20,000+ Web Queries for Code Search and Question AnsweringCode1
3D-Aware Neural Body Fitting for Occlusion Robust 3D Human Pose EstimationCode1
COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive LearningCode1
Enhancing Text-based Knowledge Graph Completion with Zero-Shot Large Language Models: A Focus on Semantic EnhancementCode1
Cross-Domain Graph Anomaly Detection via Anomaly-aware Contrastive AlignmentCode1
COPNER: Contrastive Learning with Prompt Guiding for Few-shot Named Entity RecognitionCode1
Convolutional Cross-View Pose EstimationCode1
Correct-N-Contrast: A Contrastive Approach for Improving Robustness to Spurious CorrelationsCode1
CaseGNN++: Graph Contrastive Learning for Legal Case Retrieval with Graph AugmentationCode1
CARLA: Self-supervised Contrastive Representation Learning for Time Series Anomaly DetectionCode1
CONVERT:Contrastive Graph Clustering with Reliable AugmentationCode1
Correspondence Matters for Video Referring Expression ComprehensionCode1
Contrast, Stylize and Adapt: Unsupervised Contrastive Learning Framework for Domain Adaptive Semantic SegmentationCode1
Can't Steal? Cont-Steal! Contrastive Stealing Attacks Against Image EncodersCode1
Contrast then Memorize: Semantic Neighbor Retrieval-Enhanced Inductive Multimodal Knowledge Graph CompletionCode1
An Empirical Study on Disentanglement of Negative-free Contrastive LearningCode1
Capsule Network based Contrastive Learning of Unsupervised Visual RepresentationsCode1
Contrast-Phys+: Unsupervised and Weakly-supervised Video-based Remote Physiological Measurement via Spatiotemporal ContrastCode1
ContrastVAE: Contrastive Variational AutoEncoder for Sequential RecommendationCode1
CorruptEncoder: Data Poisoning based Backdoor Attacks to Contrastive LearningCode1
An Efficient Self-Supervised Cross-View Training For Sentence EmbeddingCode1
Contrastive Video Question Answering via Video Graph TransformerCode1
Contrastive Viewpoint-aware Shape Learning for Long-term Person Re-IdentificationCode1
AD-L-JEPA: Self-Supervised Spatial World Models with Joint Embedding Predictive Architecture for Autonomous Driving with LiDAR DataCode1
Can contrastive learning avoid shortcut solutions?Code1
Contrastive Vision-Language Alignment Makes Efficient Instruction LearnerCode1
Camera-aware Proxies for Unsupervised Person Re-IdentificationCode1
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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