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 201–250 of 6661 papers

TitleStatusHype
Crafting Better Contrastive Views for Siamese Representation LearningCode2
CoST: Contrastive Learning of Disentangled Seasonal-Trend Representations for Time Series ForecastingCode2
PiCO+: Contrastive Label Disambiguation for Robust Partial Label LearningCode2
PromptBERT: Improving BERT Sentence Embeddings with PromptsCode2
C2AM: Contrastive Learning of Class-Agnostic Activation Map for Weakly Supervised Object Localization and Semantic SegmentationCode2
Are Graph Augmentations Necessary? Simple Graph Contrastive Learning for RecommendationCode2
Learning To Describe Player Form in The MLBCode2
Socially-Aware Self-Supervised Tri-Training for RecommendationCode2
SimCSE: Simple Contrastive Learning of Sentence EmbeddingsCode2
Intriguing Properties of Contrastive LossesCode2
Delving into Inter-Image Invariance for Unsupervised Visual RepresentationsCode2
Contrastive Learning for Unpaired Image-to-Image TranslationCode2
Unsupervised Learning of Visual Features by Contrasting Cluster AssignmentsCode2
Supervised Contrastive LearningCode2
A Simple Framework for Contrastive Learning of Visual RepresentationsCode2
RadiomicsRetrieval: A Customizable Framework for Medical Image Retrieval Using Radiomics FeaturesCode1
NLGCL: Naturally Existing Neighbor Layers Graph Contrastive Learning for RecommendationCode1
Vector Contrastive Learning For Pixel-Wise Pretraining In Medical VisionCode1
Refining music sample identification with a self-supervised graph neural networkCode1
TR2M: Transferring Monocular Relative Depth to Metric Depth with Language Descriptions and Scale-Oriented ContrastCode1
On the Similarities of Embeddings in Contrastive LearningCode1
Efficient Medical Vision-Language Alignment Through Adapting Masked Vision ModelsCode1
Multiple Object Stitching for Unsupervised Representation LearningCode1
C3S3: Complementary Competition and Contrastive Selection for Semi-Supervised Medical Image SegmentationCode1
A Brain Graph Foundation Model: Pre-Training and Prompt-Tuning for Any Atlas and DisorderCode1
FreRA: A Frequency-Refined Augmentation for Contrastive Learning on Time Series ClassificationCode1
Modality Curation: Building Universal Embeddings for Advanced Multimodal Information RetrievalCode1
REOBench: Benchmarking Robustness of Earth Observation Foundation ModelsCode1
DC-Seg: Disentangled Contrastive Learning for Brain Tumor Segmentation with Missing ModalitiesCode1
Breaking the Batch Barrier (B3) of Contrastive Learning via Smart Batch MiningCode1
Large Wireless Localization Model (LWLM): A Foundation Model for Positioning in 6G NetworksCode1
MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological AssessmentCode1
Hyperbolic Contrastive Learning with Model-augmentation for Knowledge-aware RecommendationCode1
Multimodal Fake News Detection: MFND Dataset and Shallow-Deep Multitask LearningCode1
ProDisc-VAD: An Efficient System for Weakly-Supervised Anomaly Detection in Video Surveillance ApplicationsCode1
Recursive KL Divergence Optimization: A Dynamic Framework for Representation LearningCode1
Semantic-Aligned Learning with Collaborative Refinement for Unsupervised VI-ReIDCode1
Relative Contrastive Learning for Sequential Recommendation with Similarity-based Positive Pair SelectionCode1
PhysioSync: Temporal and Cross-Modal Contrastive Learning Inspired by Physiological Synchronization for EEG-Based Emotion RecognitionCode1
MMHCL: Multi-Modal Hypergraph Contrastive Learning for RecommendationCode1
Intent-aware Diffusion with Contrastive Learning for Sequential RecommendationCode1
WeatherGen: A Unified Diverse Weather Generator for LiDAR Point Clouds via Spider Mamba DiffusionCode1
Towards Accurate and Interpretable Neuroblastoma Diagnosis via Contrastive Multi-scale Pathological Image AnalysisCode1
Unveiling Contrastive Learning's Capability of Neighborhood Aggregation for Collaborative FilteringCode1
Integrating Textual Embeddings from Contrastive Learning with Generative Recommender for Enhanced PersonalizationCode1
ProtoECGNet: Case-Based Interpretable Deep Learning for Multi-Label ECG Classification with Contrastive LearningCode1
Retrieval Augmented Generation with Collaborative Filtering for Personalized Text GenerationCode1
GOLLuM: Gaussian Process Optimized LLMs -- Reframing LLM Finetuning through Bayesian OptimizationCode1
ProtoGCD: Unified and Unbiased Prototype Learning for Generalized Category DiscoveryCode1
Cal or No Cal? -- Real-Time Miscalibration Detection of LiDAR and Camera SensorsCode1
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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