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 5751–5800 of 6661 papers

TitleStatusHype
Learning Street View Representations with Spatiotemporal ContrastCode0
REINFOREST: Reinforcing Semantic Code Similarity for Cross-Lingual Code Search ModelsCode0
Learning Semi-Supervised Medical Image Segmentation from Spatial RegistrationCode0
DCL: Differential Contrastive Learning for Geometry-Aware Depth SynthesisCode0
Learning Self-Supervised Representations for Label Efficient Cross-Domain Knowledge Transfer on Diabetic Retinopathy Fundus ImagesCode0
Learning Node Representations against PerturbationsCode0
Improving Time Series Encoding with Noise-Aware Self-Supervised Learning and an Efficient EncoderCode0
One-shot recognition of any material anywhere using contrastive learning with physics-based renderingCode0
Learning Representations for Clustering via Partial Information Discrimination and Cross-Level InteractionCode0
One Stone, Four Birds: A Comprehensive Solution for QA System Using Supervised Contrastive LearningCode0
Learning Oculomotor Behaviors from ScanpathCode0
Learning Multimodal Volumetric Features for Large-Scale Neuron TracingCode0
On Exploring PDE Modeling for Point Cloud Video Representation LearningCode0
Learning Label Hierarchy with Supervised Contrastive LearningCode0
Unsupervised Domain Adaptation for Brain Vessel Segmentation through Transwarp Contrastive LearningCode0
Learning Invariance from Generated Variance for Unsupervised Person Re-identificationCode0
Learning Intra and Inter-Camera Invariance for Isolated Camera Supervised Person Re-identificationCode0
Dataset Ownership Verification in Contrastive Pre-trained ModelsCode0
SimCPSR: Simple Contrastive Learning for Paper Submission Recommendation SystemCode0
Online Continual Learning via Multiple Deep Metric Learning and Uncertainty-guided Episodic Memory Replay -- 3rd Place Solution for ICCV 2021 Workshop SSLAD Track 3A Continual Object ClassificationCode0
Data-Efficient Image Recognition with Contrastive Predictive CodingCode0
Online Drift Detection with Maximum Concept DiscrepancyCode0
Learning Graph Augmentations to Learn Graph RepresentationsCode0
Data Efficient Contrastive Learning in Histopathology using Active SamplingCode0
Data Cleansing with Contrastive Learning for Vocal Note Event AnnotationsCode0
Online Unsupervised Video Object Segmentation via Contrastive Motion ClusteringCode0
Towards High-resolution 3D Anomaly Detection via Group-Level Feature Contrastive LearningCode0
Learning Genomic Sequence Representations using Graph Neural Networks over De Bruijn GraphsCode0
ActNetFormer: Transformer-ResNet Hybrid Method for Semi-Supervised Action Recognition in VideosCode0
Towards Integration of Discriminability and Robustness for Document-Level Relation ExtractionCode0
Hard-Negative Sampling for Contrastive Learning: Optimal Representation Geometry and Neural- vs Dimensional-CollapseCode0
Learning Discriminative Visual-Text Representation for Polyp Re-IdentificationCode0
Data Augmentation for Compositional Data: Advancing Predictive Models of the MicrobiomeCode0
CYBORGS: Contrastively Bootstrapping Object Representations by Grounding in SegmentationCode0
Similarity-Dissimilarity Loss for Multi-label Supervised Contrastive LearningCode0
Vision-Language Pre-Training for Boosting Scene Text DetectorsCode0
Customized Retrieval Augmented Generation and Benchmarking for EDA Tool Documentation QACode0
CultureCLIP: Empowering CLIP with Cultural Awareness through Synthetic Images and Contextualized CaptionsCode0
On the Effectiveness of Supervision in Asymmetric Non-Contrastive LearningCode0
CTSM: Combining Trait and State Emotions for Empathetic Response ModelCode0
Deep Contrastive Patch-Based Subspace Learning for Camera Image Signal ProcessingCode0
On the Efficacy of Small Self-Supervised Contrastive Models without Distillation SignalsCode0
Learning Contrastive Feature Representations for Facial Action Unit DetectionCode0
Learn from Relation Information: Towards Prototype Representation Rectification for Few-Shot Relation ExtractionCode0
CTRLStruct: Dialogue Structure Learning for Open-Domain Response GenerationCode0
Latent Processes Identification From Multi-View Time SeriesCode0
AAG: Self-Supervised Representation Learning by Auxiliary Augmentation with GNT-Xent LossCode0
CSGDN: Contrastive Signed Graph Diffusion Network for Predicting Crop Gene-phenotype AssociationsCode0
A Generalizable Deep Learning System for Cardiac MRICode0
LARP: Language Audio Relational Pre-training for Cold-Start Playlist ContinuationCode0
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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