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

Showing 62516300 of 6661 papers

TitleStatusHype
RoNID: New Intent Discovery with Generated-Reliable Labels and Cluster-friendly Representations0
Rotation-Adaptive Point Cloud Domain Generalization via Intricate Orientation Learning0
RSAM: Learning on manifolds with Riemannian Sharpness-aware Minimization0
RUEL: Retrieval-Augmented User Representation with Edge Browser Logs for Sequential Recommendation0
Run Away From your Teacher: Understanding BYOL by a Novel Self-Supervised Approach0
RUSH: Robust Contrastive Learning via Randomized Smoothing0
S2RC-GCN: A Spatial-Spectral Reliable Contrastive Graph Convolutional Network for Complex Land Cover Classification Using Hyperspectral Images0
S^3ADNet: Sequential Anomaly Detection with Pessimistic Contrastive Learning0
S^3R: Self-supervised Spectral Regression for Hyperspectral Histopathology Image Classification0
SAICL: Student Modelling with Interaction-level Auxiliary Contrastive Tasks for Knowledge Tracing and Dropout Prediction0
SALAD: Improving Robustness and Generalization through Contrastive Learning with Structure-Aware and LLM-Driven Augmented Data0
Saliency Guided Contrastive Learning on Scene Images0
SaliencyI2PLoc: saliency-guided image-point cloud localization using contrastive learning0
SAMa: Material-aware 3D Selection and Segmentation0
SAMCLR: Contrastive pre-training on complex scenes using SAM for view sampling0
SampleMatch: Drum Sample Retrieval by Musical Context0
Sample-Specific Debiasing for Better Image-Text Models0
SamToNe: Improving Contrastive Loss for Dual Encoder Retrieval Models with Same Tower Negatives0
SANCL: Multimodal Review Helpfulness Prediction with Selective Attention and Natural Contrastive Learning0
Sat2Cap: Mapping Fine-Grained Textual Descriptions from Satellite Images0
Sat2Sound: A Unified Framework for Zero-Shot Soundscape Mapping0
SATSense: Multi-Satellite Collaborative Framework for Spectrum Sensing0
Scalable Deep Metric Learning on Attributed Graphs0
SCALA: Sparsification-based Contrastive Learning for Anomaly Detection on Attributed Networks0
SCaLa: Supervised Contrastive Learning for End-to-End Speech Recognition0
Scale Contrastive Learning with Selective Attentions for Blind Image Quality Assessment0
Scale-specific auxiliary multi-task contrastive learning for deep liver vessel segmentation0
Scaling Law for Recommendation Models: Towards General-purpose User Representations0
Scaling Multimodal Pre-Training via Cross-Modality Gradient Harmonization0
SCALP -- Supervised Contrastive Learning for Cardiopulmonary Disease Classification and Localization in Chest X-rays using Patient Metadata0
SCARF: Self-Supervised Contrastive Learning using Random Feature Corruption0
SCAT: Robust Self-supervised Contrastive Learning via Adversarial Training for Text Classification0
SCDNet: Self-supervised Learning Feature-based Speaker Change Detection0
SCD-Net: Spatiotemporal Clues Disentanglement Network for Self-supervised Skeleton-based Action Recognition0
Scenario-Adaptive and Self-Supervised Model for Multi-Scenario Personalized Recommendation0
Scene Graph Contrastive Learning for Embodied Navigation0
Scene Graph Embeddings Using Relative Similarity Supervision0
SCFCRC: Simultaneously Counteract Feature Camouflage and Relation Camouflage for Fraud Detection0
SCHEMA: State CHangEs MAtter for Procedure Planning in Instructional Videos0
scMamba: A Scalable Foundation Model for Single-Cell Multi-Omics Integration Beyond Highly Variable Feature Selection0
SC-MIL: Supervised Contrastive Multiple Instance Learning for Imbalanced Classification in Pathology0
SCMPPI: Supervised Contrastive Multimodal Framework for Predicting Protein-Protein Interactions0
SCONE-GAN: Semantic Contrastive learning-based Generative Adversarial Network for an end-to-end image translation0
ScoreCL: Augmentation-Adaptive Contrastive Learning via Score-Matching Function0
Score Combining for Contrastive OOD Detection0
SMORE: Score Models for Offline Goal-Conditioned Reinforcement Learning0
SCoRe: Submodular Combinatorial Representation Learning0
SCOTCH and SODA: A Transformer Video Shadow Detection Framework0
Scrutinizing Shipment Records To Thwart Illegal Timber Trade0
SCVRL: Shuffled Contrastive Video Representation Learning0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ResNet50ImageNet Top-1 Accuracy73.6Unverified
2ResNet50ImageNet Top-1 Accuracy73Unverified
3ResNet50ImageNet Top-1 Accuracy71.1Unverified
4ResNet50ImageNet Top-1 Accuracy69.3Unverified
5ResNet50 (v2)ImageNet Top-1 Accuracy67.6Unverified
6ResNet50 (v2)ImageNet Top-1 Accuracy63.8Unverified
7ResNet50ImageNet Top-1 Accuracy63.6Unverified
8ResNet50ImageNet Top-1 Accuracy61.5Unverified
9ResNet50ImageNet Top-1 Accuracy61.5Unverified
10ResNet50 (4×)ImageNet Top-1 Accuracy61.3Unverified
#ModelMetricClaimedVerifiedStatus
110..5sec1Unverified
#ModelMetricClaimedVerifiedStatus
1IPCL (ResNet18)Accuracy (Top-1)84.77Unverified
#ModelMetricClaimedVerifiedStatus
1IPCL (ResNet18)Accuracy (Top-1)85.55Unverified