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 3751–3800 of 6661 papers

TitleStatusHype
NESS: Node Embeddings from Static SubGraphsCode1
SymBa: Symmetric Backpropagation-Free Contrastive Learning with Forward-Forward Algorithm for Optimizing ConvergenceCode0
DICNet: Deep Instance-Level Contrastive Network for Double Incomplete Multi-View Multi-Label ClassificationCode1
Automated Self-Supervised Learning for RecommendationCode2
MobileVOS: Real-Time Video Object Segmentation Contrastive Learning meets Knowledge Distillation—0
TranSG: Transformer-Based Skeleton Graph Prototype Contrastive Learning with Structure-Trajectory Prompted Reconstruction for Person Re-IdentificationCode1
Nearest-Neighbor Inter-Intra Contrastive Learning from Unlabeled Videos—0
Molecular Property Prediction by Semantic-invariant Contrastive Learning—0
Hierarchical Relationships: A New Perspective to Enhance Scene Graph GenerationCode1
DEHRFormer: Real-time Transformer for Depth Estimation and Haze Removal from Varicolored Haze Scenes—0
Unsupervised HDR Image and Video Tone Mapping via Contrastive LearningCode1
Twin Contrastive Learning with Noisy LabelsCode1
Dynamic Clustering and Cluster Contrastive Learning for Unsupervised Person Re-identificationCode1
ContraNorm: A Contrastive Learning Perspective on Oversmoothing and BeyondCode1
Accommodating Audio Modality in CLIP for Multimodal ProcessingCode0
Extending global-local view alignment for self-supervised learning with remote sensing imageryCode1
Proactive Prioritization of App Issues via Contrastive LearningCode0
User Retention-oriented Recommendation with Decision TransformerCode1
A Systematic Study of Joint Representation Learning on Protein Sequences and StructuresCode2
Generalized 3D Self-supervised Learning Framework via Prompted Foreground-Aware Feature Contrast—0
Graph Contrastive Learning under Heterophily via Graph Filters—0
FedACK: Federated Adversarial Contrastive Knowledge Distillation for Cross-Lingual and Cross-Model Social Bot DetectionCode1
CHGNN: A Semi-Supervised Contrastive Hypergraph Learning Network—0
Adaptive Supervised PatchNCE Loss for Learning H&E-to-IHC Stain Translation with Inconsistent Groundtruth Image PairsCode1
A Unified Arbitrary Style Transfer Framework via Adaptive Contrastive LearningCode1
TQ-Net: Mixed Contrastive Representation Learning For Heterogeneous Test Questions—0
Multi-task Meta Label Correction for Time Series PredictionCode0
Multi-Stage Coarse-to-Fine Contrastive Learning for Conversation Intent Induction—0
Convolutional Cross-View Pose EstimationCode1
Distortion-Disentangled Contrastive Learning—0
Learning Representation for Anomaly Detection of Vehicle Trajectories—0
An Evaluation of Non-Contrastive Self-Supervised Learning for Federated Medical Image Analysis—0
Mimic before Reconstruct: Enhancing Masked Autoencoders with Feature MimickingCode2
Contrastive Model Adaptation for Cross-Condition Robustness in Semantic SegmentationCode1
ESCL: Equivariant Self-Contrastive Learning for Sentence Representations—0
Structure-Aware Group Discrimination with Adaptive-View Graph Encoder: A Fast Graph Contrastive Learning Framework—0
Adversarial Modality Alignment Network for Cross-Modal Molecule RetrievalCode0
Semantically Consistent Multi-view Representation Learning—0
A Message Passing Perspective on Learning Dynamics of Contrastive LearningCode1
Sample-efficient Real-time Planning with Curiosity Cross-Entropy Method and Contrastive LearningCode0
Adaptive Multi-User Channel Estimation Based on Contrastive Feature Learning—0
Contrastive variational information bottleneck for aspect-based sentiment analysisCode0
SC-Block: Supervised Contrastive Blocking within Entity Resolution PipelinesCode0
Learning Efficient Coding of Natural Images with Maximum Manifold Capacity RepresentationsCode1
CleanCLIP: Mitigating Data Poisoning Attacks in Multimodal Contrastive LearningCode1
Contrastive Latent Variable Models for Neural Text GenerationCode0
CoRTX: Contrastive Framework for Real-time ExplanationCode1
Towards a Unified Theoretical Understanding of Non-contrastive Learning via Rank Differential MechanismCode0
Extended Agriculture-Vision: An Extension of a Large Aerial Image Dataset for Agricultural Pattern AnalysisCode2
Fine-Grained Classification with Noisy Labels—0
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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