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 1551–1600 of 6661 papers

TitleStatusHype
AddressCLIP: Empowering Vision-Language Models for City-wide Image Address LocalizationCode2
How to Make Cross Encoder a Good Teacher for Efficient Image-Text Retrieval?—0
CosmoCLIP: Generalizing Large Vision-Language Models for Astronomical Imaging—0
EA-VTR: Event-Aware Video-Text Retrieval—0
TIP: Tabular-Image Pre-training for Multimodal Classification with Incomplete DataCode2
ItTakesTwo: Leveraging Peer Representations for Semi-supervised LiDAR Semantic SegmentationCode1
CEIA: CLIP-Based Event-Image Alignment for Open-World Event-Based Understanding—0
Resolving Sentiment Discrepancy for Multimodal Sentiment Detection via Semantics Completion and Decomposition—0
CorMulT: A Semi-supervised Modality Correlation-aware Multimodal Transformer for Sentiment Analysis—0
HTD-Mamba: Efficient Hyperspectral Target Detection with Pyramid State Space ModelCode1
Tile Compression and Embeddings for Multi-Label Classification in GeoLifeCLEF 2024Code0
Poisson Ordinal Network for Gleason Group Estimation Using Bi-Parametric MRICode0
Sequential Contrastive Audio-Visual Learning—0
Bringing Masked Autoencoders Explicit Contrastive Properties for Point Cloud Self-Supervised LearningCode0
HyCIR: Boosting Zero-Shot Composed Image Retrieval with Synthetic Labels—0
An accurate detection is not all you need to combat label noise in web-noisy datasetsCode0
Training-free CryoET Tomogram SegmentationCode2
4D Contrastive Superflows are Dense 3D Representation LearnersCode2
Contrastive Learning of Preferences with a Contextual InfoNCE Loss—0
Self-Paced Sample Selection for Barely-Supervised Medical Image SegmentationCode0
CLAMP-ViT: Contrastive Data-Free Learning for Adaptive Post-Training Quantization of ViTsCode1
Online Drift Detection with Maximum Concept DiscrepancyCode0
Music Era Recognition Using Supervised Contrastive Learning and Artist Information—0
Language Representations Can be What Recommenders Need: Findings and PotentialsCode2
A New Brain Network Construction Paradigm for Brain Disorder via Diffusion-based Graph Contrastive Learning—0
Cross-Lingual Word Alignment for ASEAN Languages with Contrastive Learning—0
Enhanced Long-Tailed Recognition with Contrastive CutMix AugmentationCode0
The Solution for Language-Enhanced Image New Category Discovery—0
TRACE: TRansformer-based Attribution using Contrastive Embeddings in LLMs—0
Consistency and Discrepancy-Based Contrastive Tripartite Graph Learning for RecommendationsCode0
Zero-shot Object Counting with Good ExemplarsCode1
HCS-TNAS: Hybrid Constraint-driven Semi-supervised Transformer-NAS for Ultrasound Image Segmentation—0
Leveraging Graph Structures to Detect Hallucinations in Large Language ModelsCode0
An Interactive Multi-modal Query Answering System with Retrieval-Augmented Large Language ModelsCode1
DiffRetouch: Using Diffusion to Retouch on the Shoulder of Experts—0
MedRAT: Unpaired Medical Report Generation via Auxiliary Tasks—0
Supporting Cross-language Cross-project Bug Localization Using Pre-trained Language Models—0
Contrast then Memorize: Semantic Neighbor Retrieval-Enhanced Inductive Multimodal Knowledge Graph CompletionCode1
FlowCon: Out-of-Distribution Detection using Flow-Based Contrastive LearningCode0
Towards Attention-based Contrastive Learning for Audio Spoof Detection—0
A Unified Framework for 3D Scene UnderstandingCode2
Align and Aggregate: Compositional Reasoning with Video Alignment and Answer Aggregation for Video Question-Answering—0
Non-Adversarial Learning: Vector-Quantized Common Latent Space for Multi-Sequence MRICode1
A Contrastive Learning Based Convolutional Neural Network for ERP Brain-Computer Interfaces—0
Lung-CADex: Fully automatic Zero-Shot Detection and Classification of Lung Nodules in Thoracic CT Images—0
DrugCLIP: Contrastive Drug-Disease Interaction For Drug Repurposing—0
HC-GLAD: Dual Hyperbolic Contrastive Learning for Unsupervised Graph-Level Anomaly DetectionCode1
Multi-Grained Contrast for Data-Efficient Unsupervised Representation LearningCode1
CGRclust: Chaos Game Representation for Twin Contrastive Clustering of Unlabelled DNA SequencesCode0
SignCLIP: Connecting Text and Sign Language by Contrastive LearningCode1
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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