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 3451–3500 of 6661 papers

TitleStatusHype
VCM: Vision Concept Modeling Based on Implicit Contrastive Learning with Vision-Language Instruction Fine-Tuning—0
VECO 2.0: Cross-lingual Language Model Pre-training with Multi-granularity Contrastive Learning—0
Vehicle Trajectory Prediction by Transfer Learning of Semi-Supervised Models—0
VGFL-SA: Vertical Graph Federated Learning Structure Attack Based on Contrastive Learning—0
Vi2CLR: Video and Image for Visual Contrastive Learning of Representation—0
Video-based Contrastive Learning on Decision Trees: from Action Recognition to Autism Diagnosis—0
Video Salient Object Detection via Contrastive Features and Attention Modules—0
Video sentence grounding with temporally global textual knowledge—0
VidLPRO: A Video-Language Pre-training Framework for Robotic and Laparoscopic Surgery—0
ViEEG: Hierarchical Neural Coding with Cross-Modal Progressive Enhancement for EEG-Based Visual Decoding—0
View-Invariant Skeleton-based Action Recognition via Global-Local Contrastive Learning—0
Explicit View-labels Matter: A Multifacet Complementarity Study of Multi-view Clustering—0
Viewpoint Rosetta Stone: Unlocking Unpaired Ego-Exo Videos for View-invariant Representation Learning—0
ViFiCon: Vision and Wireless Association Via Self-Supervised Contrastive Learning—0
ViFi-ReID: A Two-Stream Vision-WiFi Multimodal Approach for Person Re-identification—0
VIGraph: Generative Self-supervised Learning for Class-Imbalanced Node Classification—0
ViLEM: Visual-Language Error Modeling for Image-Text Retrieval—0
Virtual Fusion with Contrastive Learning for Single Sensor-based Activity Recognition—0
Vision Language Pre-training by Contrastive Learning with Cross-Modal Similarity Regulation—0
Vision-Language Modeling Meets Remote Sensing: Models, Datasets and Perspectives—0
Vision-Language Pre-training with Object Contrastive Learning for 3D Scene Understanding—0
ViSTA: Vision and Scene Text Aggregation for Cross-Modal Retrieval—0
VisTA: Vision-Text Alignment Model with Contrastive Learning using Multimodal Data for Evidence-Driven, Reliable, and Explainable Alzheimer's Disease Diagnosis—0
Visual Commonsense based Heterogeneous Graph Contrastive Learning—0
Visual Encoding and Debiasing for CTR Prediction—0
Visual Imitation Learning with Calibrated Contrastive Representation—0
Visualizing the Diversity of Representations Learned by Bayesian Neural Networks—0
Visual Question Answering in the Medical Domain—0
Visual-Semantic Contrastive Alignment for Few-Shot Image Classification—0
Visual Transformation Aided Contrastive Learning for Video-Based Kinship Verification—0
VLDeformer: Vision-Language Decomposed Transformer for Fast Cross-Modal Retrieval—0
VLMixer: Unpaired Vision-Language Pre-training via Cross-Modal CutMix—0
VMAS: Video-to-Music Generation via Semantic Alignment in Web Music Videos—0
Volumetric Supervised Contrastive Learning for Seismic Semantic Segmentation—0
Voxel-level Siamese Representation Learning for Abdominal Multi-Organ Segmentation—0
VPN: Video Provenance Network for Robust Content Attribution—0
Wasserstein Contrastive Representation Distillation—0
Watching Too Much Television is Good: Self-Supervised Audio-Visual Representation Learning from Movies and TV Shows—0
Watchog: A Light-weight Contrastive Learning based Framework for Column Annotation—0
Watermarking Pre-trained Encoders in Contrastive Learning—0
Wav2vec-Switch: Contrastive Learning from Original-noisy Speech Pairs for Robust Speech Recognition—0
Wavelet-Decoupling Contrastive Enhancement Network for Fine-Grained Skeleton-Based Action Recognition—0
WCL-BBCD: A Contrastive Learning and Knowledge Graph Approach to Named Entity Recognition—0
Weakly-Supervised Audio-Visual Segmentation—0
Weakly-Supervised Audio-Visual Video Parsing with Prototype-based Pseudo-Labeling—0
Weakly-supervised Generative Adversarial Networks for medical image classification—0
Weakly Supervised Person Search with Region Siamese Networks—0
Weakly-supervised Semantic Segmentation via Dual-stream Contrastive Learning of Cross-image Contextual Information—0
Weakly Supervised Temporal Sentence Grounding via Positive Sample Mining—0
Weakly-Supervised Text-driven Contrastive Learning for Facial Behavior Understanding—0
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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