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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1201–1250 of 6661 papers

TitleStatusHype
Deep Contrastive One-Class Time Series Anomaly DetectionCode1
Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed RecognitionCode1
DUET: Cross-modal Semantic Grounding for Contrastive Zero-shot LearningCode1
Embedding contrastive unsupervised features to cluster in- and out-of-distribution noise in corrupted image datasetsCode1
Reading and Writing: Discriminative and Generative Modeling for Self-Supervised Text RecognitionCode1
BadHash: Invisible Backdoor Attacks against Deep Hashing with Clean LabelCode1
Self-Supervised Learning for Multimedia RecommendationCode1
FedIIC: Towards Robust Federated Learning for Class-Imbalanced Medical Image ClassificationCode1
Reducing Annotation Need in Self-Explanatory Models for Lung Nodule DiagnosisCode1
Vision Transformer for Contrastive ClusteringCode1
Wiener Graph Deconvolutional Network Improves Graph Self-Supervised LearningCode1
VLCap: Vision-Language with Contrastive Learning for Coherent Video Paragraph CaptioningCode1
Language Models as Knowledge EmbeddingsCode1
SLIC: Self-Supervised Learning with Iterative Clustering for Human Action VideosCode1
CLAMP: Prompt-based Contrastive Learning for Connecting Language and Animal PoseCode1
Utilizing Expert Features for Contrastive Learning of Time-Series RepresentationsCode1
Towards Galaxy Foundation Models with Hybrid Contrastive LearningCode1
Robust Task Representations for Offline Meta-Reinforcement Learning via Contrastive LearningCode1
Panoramic Panoptic Segmentation: Insights Into Surrounding Parsing for Mobile Agents via Unsupervised Contrastive LearningCode1
Conditioned and Composed Image Retrieval Combining and Partially Fine-Tuning CLIP-Based FeaturesCode1
Learning Fair Representation via Distributional Contrastive DisentanglementCode1
MET: Masked Encoding for Tabular DataCode1
Let Invariant Rationale Discovery Inspire Graph Contrastive LearningCode1
NCAGC: A Neighborhood Contrast Framework for Attributed Graph ClusteringCode1
Discrete Contrastive Diffusion for Cross-Modal Music and Image GenerationCode1
Text-Aware End-to-end Mispronunciation Detection and DiagnosisCode1
Contrastive Learning for Unsupervised Domain Adaptation of Time SeriesCode1
An Empirical Study on Disentanglement of Negative-free Contrastive LearningCode1
I'm Me, We're Us, and I'm Us: Tri-directional Contrastive Learning on HypergraphsCode1
COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive LearningCode1
CO^3: Cooperative Unsupervised 3D Representation Learning for Autonomous DrivingCode1
Improving Contrastive Learning of Sentence Embeddings with Case-Augmented Positives and Retrieved NegativesCode1
Bootstrapping Semi-supervised Medical Image Segmentation with Anatomical-aware Contrastive DistillationCode1
From t-SNE to UMAP with contrastive learningCode1
Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group DiscriminationCode1
Hyperspherical Consistency RegularizationCode1
Strongly Augmented Contrastive ClusteringCode1
Cross-View Language Modeling: Towards Unified Cross-Lingual Cross-Modal Pre-trainingCode1
CrossCBR: Cross-view Contrastive Learning for Bundle RecommendationCode1
Dog nose print matching with dual global descriptor based on Contrastive LearningCode1
SOM-CPC: Unsupervised Contrastive Learning with Self-Organizing Maps for Structured Representations of High-Rate Time SeriesCode1
Self-Supervised Visual Representation Learning with Semantic GroupingCode1
A Closer Look at Self-Supervised Lightweight Vision TransformersCode1
Multimodal Masked Autoencoders Learn Transferable RepresentationsCode1
Target-aware Abstractive Related Work Generation with Contrastive LearningCode1
Learning Dialogue Representations from Consecutive UtterancesCode1
Cross-Architecture Self-supervised Video Representation LearningCode1
BppAttack: Stealthy and Efficient Trojan Attacks against Deep Neural Networks via Image Quantization and Contrastive Adversarial LearningCode1
Contrastive Learning with Boosted MemorizationCode1
Optimizing Test-Time Query Representations for Dense RetrievalCode1
Show:102550
← PrevPage 25 of 134Next →
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