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 801–850 of 6661 papers

TitleStatusHype
Collaborating Domain-shared and Target-specific Feature Clustering for Cross-domain 3D Action RecognitionCode1
FakeCLR: Exploring Contrastive Learning for Solving Latent Discontinuity in Data-Efficient GANsCode1
Behavior Contrastive Learning for Unsupervised Skill DiscoveryCode1
Contrastive Prototypical Network with Wasserstein Confidence PenaltyCode1
A Self-Supervised Gait Encoding Approach with Locality-Awareness for 3D Skeleton Based Person Re-IdentificationCode1
FashionViL: Fashion-Focused Vision-and-Language Representation LearningCode1
A Contrastive Cross-Channel Data Augmentation Framework for Aspect-based Sentiment AnalysisCode1
ChatRetriever: Adapting Large Language Models for Generalized and Robust Conversational Dense RetrievalCode1
A Self-supervised Method for Entity AlignmentCode1
CoLA: Weakly-Supervised Temporal Action Localization with Snippet Contrastive LearningCode1
Reinforcement Learning Friendly Vision-Language Model for MinecraftCode1
FedIIC: Towards Robust Federated Learning for Class-Imbalanced Medical Image ClassificationCode1
BECLR: Batch Enhanced Contrastive Few-Shot LearningCode1
FedX: Unsupervised Federated Learning with Cross Knowledge DistillationCode1
Contrastive Positive Sample Propagation along the Audio-Visual Event LineCode1
Contrastive Quantization with Code Memory for Unsupervised Image RetrievalCode1
CIC: Contrastive Intrinsic Control for Unsupervised Skill DiscoveryCode1
Finding Order in Chaos: A Novel Data Augmentation Method for Time Series in Contrastive LearningCode1
Fine-grained Temporal Contrastive Learning for Weakly-supervised Temporal Action LocalizationCode1
Finetuning CLIP to Reason about Pairwise DifferencesCode1
Contrastive Retrospection: honing in on critical steps for rapid learning and generalization in RLCode1
FLIP: Cross-domain Face Anti-spoofing with Language GuidanceCode1
Contrastive Multiview CodingCode1
Following the Autoregressive Nature of LLM Embeddings via Compression and AlignmentCode1
Contrastive Multimodal Fusion with TupleInfoNCECode1
Fragment-based Pretraining and Finetuning on Molecular GraphsCode1
A Simple and Effective Self-Supervised Contrastive Learning Framework for Aspect DetectionCode1
Frequency-Based Alignment of EEG and Audio Signals Using Contrastive Learning and SincNet for Auditory Attention DetectionCode1
CL4CTR: A Contrastive Learning Framework for CTR PredictionCode1
Frequency-Masked Embedding Inference: A Non-Contrastive Approach for Time Series Representation LearningCode1
Contrastive Neural Processes for Self-Supervised LearningCode1
CLIP2Point: Transfer CLIP to Point Cloud Classification with Image-Depth Pre-trainingCode1
A Simple Contrastive Learning Objective for Alleviating Neural Text DegenerationCode1
BCE-Net: Reliable Building Footprints Change Extraction based on Historical Map and Up-to-Date Images using Contrastive LearningCode1
A simple, efficient and scalable contrastive masked autoencoder for learning visual representationsCode1
CLAMP-ViT: Contrastive Data-Free Learning for Adaptive Post-Training Quantization of ViTsCode1
Multi-level Feature Learning for Contrastive Multi-view ClusteringCode1
CLAP: Isolating Content from Style through Contrastive Learning with Augmented PromptsCode1
Contrastive Object-level Pre-training with Spatial Noise Curriculum LearningCode1
CLARA: Multilingual Contrastive Learning for Audio Representation AcquisitionCode1
GCC: Graph Contrastive Coding for Graph Neural Network Pre-TrainingCode1
GCFAgg: Global and Cross-view Feature Aggregation for Multi-view ClusteringCode1
A Simple Graph Contrastive Learning Framework for Short Text ClassificationCode1
CLASP: Contrastive Language-Speech Pretraining for Multilingual Multimodal Information RetrievalCode1
Contrastive Meta Learning with Behavior Multiplicity for RecommendationCode1
Generalized Category Discovery with Large Language Models in the LoopCode1
A Broad Study on the Transferability of Visual Representations with Contrastive LearningCode1
Contrastive Model Adaptation for Cross-Condition Robustness in Semantic SegmentationCode1
A Simple yet Effective Relation Information Guided Approach for Few-Shot Relation ExtractionCode1
CLIP2Scene: Towards Label-efficient 3D Scene Understanding by CLIPCode1
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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