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 5751–5800 of 6661 papers

TitleStatusHype
Contrastive Learning is Just Meta-Learning—0
Fine-grained Software Vulnerability Detection via Information Theory and Contrastive Learning—0
AAVAE: Augmentation-Augmented Variational Autoencoders—0
Contrastive Label Disambiguation for Partial Label LearningCode1
Multi-Domain Self-Supervised Learning—0
Information-Aware Time Series Meta-Contrastive Learning—0
Self-Contrastive Learning—0
A Transferable General-Purpose Predictor for Neural Architecture Search—0
A Rate-Distortion Approach to Domain Generalization—0
Context-invariant, multi-variate time series representations—0
SimMER: Simple Maximization of Entropy and Rank for Self-supervised Representation Learning—0
Interrogating Paradigms in Self-supervised Graph Representation Learning—0
Chaos is a Ladder: A New Understanding of Contrastive Learning—0
The Details Matter: Preventing Class Collapse in Supervised Contrastive Learning—0
Approximate Bijective Correspondence for isolating factors of variationCode0
Understanding Self-supervised Learning via Information Bottleneck Principle—0
Rethinking Temperature in Graph Contrastive LearningCode0
Inductive-Biases for Contrastive Learning of Disentangled Representations—0
f-Mutual Information Contrastive Learning—0
SynCLR: A Synthesis Framework for Contrastive Learning of out-of-domain Speech Representations—0
Data-Efficient Contrastive Learning by Differentiable Hard Sample and Hard Positive Pair Generation—0
Contrastive Quant: Quantization Makes Stronger Contrastive Learning—0
Contrastive Pre-training for Zero-Shot Information Retrieval—0
ESCo: Towards Provably Effective and Scalable Contrastive Representation Learning—0
How does Contrastive Pre-training Connect Disparate Domains?—0
Unsupervised Vision-Language Grammar Induction with Shared Structure Modeling—0
Identity-Disentangled Adversarial Augmentation for Self-supervised Learning—0
Contrastive Video-Language Segmentation—0
Hybrid Dynamic Contrast and Probability Distillation for Unsupervised Person Re-Id—0
Towards Communication-Efficient and Privacy-Preserving Federated Representation Learning—0
Boost-RS: Boosted Embeddings for Recommender Systems and its Application to Enzyme-Substrate Interaction PredictionCode0
A Contrastive Learning Approach to Auroral Identification and Classification—0
Modelling Neighbor Relation in Joint Space-Time Graph for Video Correspondence Learning—0
The JHU submission to VoxSRC-21: Track 3—0
Dynamic Modeling of Hand-Object Interactions via Tactile Sensing.—0
Click-through Rate Prediction with Auto-Quantized Contrastive Learning—0
Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillationsCode1
Compressive Visual RepresentationsCode1
Self-Supervised Video Representation Learning by Video Incoherence Detection—0
DialogueCSE: Dialogue-based Contrastive Learning of Sentence EmbeddingsCode1
Cluster Analysis with Deep Embeddings and Contrastive Learning—0
Hard-sample Guided Hybrid Contrast Learning for Unsupervised Person Re-IdentificationCode1
Weakly Supervised Contrastive Learning for Chest X-Ray Report GenerationCode1
Contrastive Learning for Mitochondria Segmentation—0
Dense Contrastive Visual-Linguistic Pretraining—0
GeomGCL: Geometric Graph Contrastive Learning for Molecular Property PredictionCode1
Self-supervised Learning for Semi-supervised Temporal Language Grounding—0
Long Short View Feature Decomposition via Contrastive Video Representation Learning—0
Learning Contrastive Representation for Semantic Correspondence—0
Contrastive Learning for Fair Representations—0
Show:102550
← PrevPage 116 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