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 5801–5850 of 6661 papers

TitleStatusHype
Generating Compositional Color Representations from Text—0
DyStyle: Dynamic Neural Network for Multi-Attribute-Conditioned Style EditingCode1
VPN: Video Provenance Network for Robust Content Attribution—0
AutoGCL: Automated Graph Contrastive Learning via Learnable View GeneratorsCode1
Homography augumented momentum constrastive learning for SAR image retrieval—0
On the Importance of Distractors for Few-Shot ClassificationCode1
Contrastive Learning of Subject-Invariant EEG Representations for Cross-Subject Emotion Recognition—0
MirrorWiC: On Eliciting Word-in-Context Representations from Pretrained Language ModelsCode1
Adversarial Training with Contrastive Learning in NLP—0
CLIFF: Contrastive Learning for Improving Faithfulness and Factuality in Abstractive SummarizationCode0
Multilingual Molecular Representation Learning via Contrastive Pre-training—0
Interest-oriented Universal User Representation via Contrastive Learning—0
Intra-Inter Subject Self-supervised Learning for Multivariate Cardiac Signals—0
Semi-Supervised Few-Shot Intent Classification and Slot Filling—0
Pointly-supervised 3D Scene Parsing with Viewpoint BottleneckCode1
Dense Semantic Contrast for Self-Supervised Visual Representation Learning—0
Self-supervised Contrastive Learning for EEG-based Sleep StagingCode1
Federated Contrastive Learning for Decentralized Unlabeled Medical Images—0
Semi-supervised Contrastive Learning for Label-efficient Medical Image SegmentationCode1
SupCL-Seq: Supervised Contrastive Learning for Downstream Optimized Sequence RepresentationsCode1
Deep Bregman Divergence for Contrastive Learning of Visual Representations—0
CONTaiNER: Few-Shot Named Entity Recognition via Contrastive LearningCode1
Improving Gradient-based Adversarial Training for Text Classification by Contrastive Learning and Auto-Encoder—0
Camera-Tracklet-Aware Contrastive Learning for Unsupervised Vehicle Re-IdentificationCode0
KFCNet: Knowledge Filtering and Contrastive Learning Network for Generative Commonsense Reasoning—0
Identifying partial mouse brain microscopy images from Allen reference atlas using a contrastively learned semantic spaceCode0
Few-Shot Intent Detection via Contrastive Pre-Training and Fine-TuningCode1
Contrastive Learning for Context-aware Neural Machine TranslationUsing Coreference Information—0
Weakly Supervised Person Search with Region Siamese Networks—0
Exploring Task Difficulty for Few-Shot Relation ExtractionCode1
Pairwise Supervised Contrastive Learning of Sentence RepresentationsCode1
Learning To Describe Player Form in The MLBCode2
Contrastive Quantization with Code Memory for Unsupervised Image RetrievalCode1
Efficient Contrastive Learning via Novel Data Augmentation and Curriculum LearningCode1
Attention-based Contrastive Learning for Winograd SchemasCode0
TACS: Taxonomy Adaptive Cross-Domain Semantic SegmentationCode1
Topic-Aware Contrastive Learning for Abstractive Dialogue SummarizationCode1
Generalised Unsupervised Domain Adaptation of Neural Machine Translation with Cross-Lingual Data SelectionCode0
Supervised Contrastive Learning for Detecting Anomalous Driving Behaviours from Multimodal VideosCode0
ESimCSE: Enhanced Sample Building Method for Contrastive Learning of Unsupervised Sentence EmbeddingCode1
Preservational Learning Improves Self-supervised Medical Image Models by Reconstructing Diverse ContextsCode1
Smoothed Contrastive Learning for Unsupervised Sentence EmbeddingCode1
Dynamic Modeling of Hand-Object Interactions via Tactile Sensing—0
M5Product: Self-harmonized Contrastive Learning for E-commercial Multi-modal Pretraining—0
Sequence Level Contrastive Learning for Text SummarizationCode1
X-GOAL: Multiplex Heterogeneous Graph Prototypical Contrastive Learning—0
Unpaired Deep Image Deraining Using Dual Contrastive Learning—0
Hyper Meta-Path Contrastive Learning for Multi-Behavior Recommendation—0
Contrastive Learning with Temporal Correlated Medical Images: A Case Study using Lung Segmentation in Chest X-RaysCode0
Self-supervised Product Quantization for Deep Unsupervised Image RetrievalCode0
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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