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 3101–3150 of 6661 papers

TitleStatusHype
Generating Faithful Text From a Knowledge Graph with Noisy Reference Text—0
Contrastive Learning for Cross-modal Artist Retrieval—0
BEV-DG: Cross-Modal Learning under Bird's-Eye View for Domain Generalization of 3D Semantic Segmentation—0
CSPM: A Contrastive Spatiotemporal Preference Model for CTR Prediction in On-Demand Food Delivery Services—0
Counterfactual Cross-modality Reasoning for Weakly Supervised Video Moment LocalizationCode0
AD-CLIP: Adapting Domains in Prompt Space Using CLIPCode1
Unlocking the diagnostic potential of electrocardiograms through information transfer from cardiac magnetic resonance imagingCode1
Cross-view Semantic Alignment for Livestreaming Product RecognitionCode0
Slot Induction via Pre-trained Language Model Probing and Multi-level Contrastive LearningCode0
Induction Network: Audio-Visual Modality Gap-Bridging for Self-Supervised Sound Source LocalizationCode0
Revisiting Disentanglement and Fusion on Modality and Context in Conversational Multimodal Emotion Recognition—0
D3G: Exploring Gaussian Prior for Temporal Sentence Grounding with Glance AnnotationCode1
Exploring Transformers for Open-world Instance Segmentation—0
Expression Prompt Collaboration Transformer for Universal Referring Video Object SegmentationCode0
A Bi-directional Multi-hop Inference Model for Joint Dialog Sentiment Classification and Act Recognition—0
Prompted Contrast with Masked Motion Modeling: Towards Versatile 3D Action Representation LearningCode1
A Hybrid CNN-Transformer Architecture with Frequency Domain Contrastive Learning for Image Deraining—0
Multi-Label Self-Supervised Learning with Scene Images—0
Cross-Silo Prototypical Calibration for Federated Learning with Non-IID DataCode1
Hierarchical Contrastive Learning with Multiple Augmentation for Sequential Recommendation—0
SSL-SoilNet: A Hybrid Transformer-based Framework with Self-Supervised Learning for Large-scale Soil Organic Carbon PredictionCode1
Towards General Text Embeddings with Multi-stage Contrastive Learning—0
Local Structure-aware Graph Contrastive Representation Learning—0
Exploring Visual Pre-training for Robot Manipulation: Datasets, Models and Methods—0
All-in-one Multi-degradation Image Restoration Network via Hierarchical Degradation Representation—0
Source-free Domain Adaptive Human Pose EstimationCode1
Semi-supervised Contrastive Regression for Estimation of Eye Gaze—0
One-stage Low-resolution Text Recognition with High-resolution Knowledge TransferCode1
Bootstrapping Contrastive Learning Enhanced Music Cold-Start Matching—0
From Fake to Hyperpartisan News Detection Using Domain Adaptation—0
Learning Referring Video Object Segmentation from Weak Annotation—0
Efficient Labelling of Affective Video Datasets via Few-Shot & Multi-Task Contrastive LearningCode0
Adapting to Change: Robust Counterfactual Explanations in Dynamic Data LandscapesCode0
Learning beyond sensations: how dreams organize neuronal representations—0
COMICS: End-to-end Bi-grained Contrastive Learning for Multi-face Forgery DetectionCode0
Unsupervised Representation Learning for Time Series: A ReviewCode1
Orientation-Guided Contrastive Learning for UAV-View Geo-Localisation—0
A Multi-Source Data Fusion-based Semantic Segmentation Model for Relic Landslide Detection—0
Three Factors to Improve Out-of-Distribution Detection—0
Graph Anomaly Detection at Group Level: A Topology Pattern Enhanced Unsupervised Approach—0
ADS-Cap: A Framework for Accurate and Diverse Stylized Captioning with Unpaired Stylistic CorporaCode0
ELIXR: Towards a general purpose X-ray artificial intelligence system through alignment of large language models and radiology vision encoders—0
Dynamically Scaled Temperature in Self-Supervised Contrastive LearningCode0
Self-Supervised Contrastive BERT Fine-tuning for Fusion-based Reviewed-Item RetrievalCode0
Center Contrastive Loss for Metric Learning—0
Graph Embedding Dynamic Feature-based Supervised Contrastive Learning of Transient Stability for Changing Power Grid Topologies—0
Graph Contrastive Learning with Generative Adversarial Network—0
Relational Contrastive Learning for Scene Text RecognitionCode1
Can Self-Supervised Representation Learning Methods Withstand Distribution Shifts and Corruptions?Code0
CroSSL: Cross-modal Self-Supervised Learning for Time-series through Latent MaskingCode1
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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