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 6101–6150 of 6661 papers

TitleStatusHype
Contrastive Learning for OOD in Object detectionCode0
Heterogeneous Contrastive LearningCode0
Are Existing Out-Of-Distribution Techniques Suitable for Network Intrusion Detection?Code0
Contrastive Learning for Online Semi-Supervised General Continual LearningCode0
Harnessing Shared Relations via Multimodal Mixup Contrastive Learning for Multimodal ClassificationCode0
ProtoX: Explaining a Reinforcement Learning Agent via PrototypingCode0
ProtSi: Prototypical Siamese Network with Data Augmentation for Few-Shot Subjective Answer EvaluationCode0
Harnessing Joint Rain-/Detail-aware Representations to Eliminate Intricate RainsCode0
StablePT: Towards Stable Prompting for Few-shot Learning via Input SeparationCode0
Provable Ordering and Continuity in Vision-Language Pretraining for Generalizable Embodied AgentsCode0
Contrastive Learning for Object DetectionCode0
Stain-aware Domain Alignment for Imbalance Blood Cell ClassificationCode0
Harmony: A Joint Self-Supervised and Weakly-Supervised Framework for Learning General Purpose Visual RepresentationsCode0
Provable Training for Graph Contrastive LearningCode0
CHMATCH: Contrastive Hierarchical Matching and Robust Adaptive Threshold Boosted Semi-Supervised LearningCode0
Adversarial Examples can be Effective Data Augmentation for Unsupervised Machine LearningCode0
Chasing Fairness in Graphs: A GNN Architecture PerspectiveCode0
Pseudo-Label Enhanced Prototypical Contrastive Learning for Uniformed Intent DiscoveryCode0
Beyond Random Augmentations: Pretraining with Hard ViewsCode0
Pseudolabel guided pixels contrast for domain adaptive semantic segmentationCode0
Contrastive learning for natural language-based vehicle retrievalCode0
Channel-aware Contrastive Conditional Diffusion for Multivariate Probabilistic Time Series ForecastingCode0
Adversarial Bootstrapped Question Representation Learning for Knowledge TracingCode0
Transferable Availability Poisoning AttacksCode0
Pylon: Semantic Table Union Search in Data LakesCode0
Pyramid Self-attention Polymerization Learning for Semi-supervised Skeleton-based Action RecognitionCode0
QA Domain Adaptation using Hidden Space Augmentation and Self-Supervised Contrastive AdaptationCode0
StatioCL: Contrastive Learning for Time Series via Non-Stationary and Temporal ContrastCode0
Architecture Matters: Uncovering Implicit Mechanisms in Graph Contrastive LearningCode0
Hard Negative Contrastive Learning for Fine-Grained Geometric Understanding in Large Multimodal ModelsCode0
A Contrastive Variational Graph Auto-Encoder for Node ClusteringCode0
Advancing Semantic Textual Similarity Modeling: A Regression Framework with Translated ReLU and Smooth K2 LossCode0
TransformCode: A Contrastive Learning Framework for Code Embedding via Subtree TransformationCode0
Contrastive Learning for Multi-Object Tracking with TransformersCode0
Transform, Contrast and Tell: Coherent Entity-Aware Multi-Image CaptioningCode0
HaLP: Hallucinating Latent Positives for Skeleton-based Self-Supervised Learning of ActionsCode0
STELLAR: Siamese Multi-Headed Attention Neural Networks for Overcoming Temporal Variations and Device Heterogeneity with Indoor LocalizationCode0
Unsupervised Social Event Detection via Hybrid Graph Contrastive Learning and Reinforced Incremental ClusteringCode0
Guidelines for Augmentation Selection in Contrastive Learning for Time Series ClassificationCode0
Contrastive Learning for Lane Detection via cross-similarityCode0
Quantile-based Maximum Likelihood Training for Outlier DetectionCode0
Your Contrastive Learning Is Secretly Doing Stochastic Neighbor EmbeddingCode0
CGRclust: Chaos Game Representation for Twin Contrastive Clustering of Unlabelled DNA SequencesCode0
Quantum-inspired Embeddings Projection and Similarity Metrics for Representation LearningCode0
CFL-Net: Image Forgery Localization Using Contrastive LearningCode0
GS-EMA: Integrating Gradient Surgery Exponential Moving Average with Boundary-Aware Contrastive Learning for Enhanced Domain Generalization in Aneurysm SegmentationCode0
Grounding Bodily Awareness in Visual Representations for Efficient Policy LearningCode0
Text Conditioned Symbolic Drumbeat Generation using Latent Diffusion ModelsCode0
Advancing Brainwave-Based Biometrics: A Large-Scale, Multi-Session EvaluationCode0
VOILA: Complexity-Aware Universal Segmentation of CT images by Voxel Interacting with LanguageCode0
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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