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 3801–3850 of 6661 papers

TitleStatusHype
NCL: Textual Backdoor Defense Using Noise-augmented Contrastive Learning—0
Generalized Semantic Segmentation by Self-Supervised Source Domain Projection and Multi-Level Contrastive LearningCode0
Pyramid Pixel Context Adaption Network for Medical Image Classification with Supervised Contrastive Learning—0
On the Provable Advantage of Unsupervised Pretraining—0
Hierarchical discriminative learning improves visual representations of biomedical microscopy—0
Heterogeneous Graph Contrastive Learning for RecommendationCode1
Multi-Task Self-Supervised Time-Series Representation Learning—0
CTRLStruct: Dialogue Structure Learning for Open-Domain Response GenerationCode0
Ego-Vehicle Action Recognition based on Semi-Supervised Contrastive Learning—0
Unsupervised Meta-Learning via Few-shot Pseudo-supervised Contrastive LearningCode1
ArCL: Enhancing Contrastive Learning with Augmentation-Robust Representations—0
Rethinking the Effect of Data Augmentation in Adversarial Contrastive LearningCode1
Benchmarking Self-Supervised Contrastive Learning Methods for Image-Based Plant PhenotypingCode0
Can representation learning for multimodal image registration be improved by supervision of intermediate layers?—0
PE-GAN: Prior Embedding GAN for PXD images at Belle IICode0
Multimodal Industrial Anomaly Detection via Hybrid FusionCode2
GUESR: A Global Unsupervised Data-Enhancement with Bucket-Cluster Sampling for Sequential Recommendation—0
Edge computing on TPU for brain implant signal analysisCode0
The Trade-off between Universality and Label Efficiency of Representations from Contrastive LearningCode0
Self-Supervised Interest Transfer Network via Prototypical Contrastive Learning for RecommendationCode0
Mask3D: Pre-training 2D Vision Transformers by Learning Masked 3D Priors—0
Dissolving Is Amplifying: Towards Fine-Grained Anomaly DetectionCode1
CLR-GAM: Contrastive Point Cloud Learning with Guided Augmentation and Feature Mapping—0
A Prototypical Semantic Decoupling Method via Joint Contrastive Learning for Few-Shot Name Entity Recognition—0
Layer Grafted Pre-training: Bridging Contrastive Learning And Masked Image Modeling For Label-Efficient RepresentationsCode1
Revisit Out-Of-Vocabulary Problem for Slot Filling: A Unified Contrastive Frameword with Multi-level Data Augmentations—0
A Comparative Analysis Of Latent Regressor Losses For Singing Voice Conversion—0
MPS-AMS: Masked Patches Selection and Adaptive Masking Strategy Based Self-Supervised Medical Image Segmentation—0
Contrastive Video Question Answering via Video Graph TransformerCode1
MCoCo: Multi-level Consistency Collaborative Multi-view Clustering—0
DCLP: Neural Architecture Predictor with Curriculum Contrastive LearningCode0
Cross-modal Contrastive Learning for Multimodal Fake News DetectionCode1
Introducing Depth into Transformer-based 3D Object Detection—0
Knowledge-infused Contrastive Learning for Urban Imagery-based Socioeconomic PredictionCode1
Flexible Phase Dynamics for Bio-Plausible Contrastive LearningCode0
Improving Sentence Similarity Estimation for Unsupervised Extractive SummarizationCode0
Language-Driven Representation Learning for RoboticsCode2
Amortised Invariance Learning for Contrastive Self-SupervisionCode0
An Iterative Classification and Semantic Segmentation Network for Old Landslide Detection Using High-Resolution Remote Sensing Images—0
Generalization Analysis for Contrastive Representation Learning—0
Learning Visual Representations via Language-Guided SamplingCode1
Attention Mechanism for Contrastive Learning in GAN-based Image-to-Image Translation—0
Cross-Modal Retrieval with Partially Mismatched PairsCode1
Saliency Guided Contrastive Learning on Scene Images—0
DMMG: Dual Min-Max Games for Self-Supervised Skeleton-Based Action Recognition—0
K-Diag: Knowledge-enhanced Disease Diagnosis in Radiographic Imaging—0
ACE: Zero-Shot Image to Image Translation via Pretrained Auto-Contrastive-EncoderCode0
Test-Time Distribution Normalization for Contrastively Learned Vision-language ModelsCode1
Novel Class Discovery: an Introduction and Key ConceptsCode0
Contrastive Representation Learning for Acoustic Parameter Estimation—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