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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 4551–4560 of 6661 papers

Title	Date	Tasks	Status	Hype
MimCo: Masked Image Modeling Pre-training with Contrastive Teacher	Sep 7, 2022	Contrastive LearningSelf-Supervised Learning	—Unverified	0
Language-aware Domain Generalization Network for Cross-Scene Hyperspectral Image Classification	Sep 6, 2022	Contrastive LearningDomain Generalization	—Unverified	0
XSimGCL: Towards Extremely Simple Graph Contrastive Learning for Recommendation	Sep 6, 2022	Contrastive Learning	CodeCode Available	2
Progressive Domain Adaptation with Contrastive Learning for Object Detection in the Satellite Imagery	Sep 6, 2022	Contrastive LearningDomain Adaptation	—Unverified	0
Multimodal contrastive learning for remote sensing tasks	Sep 6, 2022	Contrastive Learning	—Unverified	0
SimCLF: A Simple Contrastive Learning Framework for Function-level Binary Embeddings	Sep 6, 2022	Compiler OptimizationContrastive Learning	CodeCode Available	0
Design of the topology for contrastive visual-textual alignment	Sep 5, 2022	Contrastive LearningImage-to-Text Retrieval	CodeCode Available	0
Supervised Contrastive Learning to Classify Paranasal Anomalies in the Maxillary Sinus	Sep 5, 2022	Anomaly ClassificationContrastive Learning	—Unverified	0
Representative Image Feature Extraction via Contrastive Learning Pretraining for Chest X-ray Report Generation	Sep 4, 2022	Contrastive LearningMedical Report Generation	—Unverified	0
SCL-RAI: Span-based Contrastive Learning with Retrieval Augmented Inference for Unlabeled Entity Problem in NER	Sep 4, 2022	Contrastive Learningnamed-entity-recognition	CodeCode Available	1

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All datasets imagenet-1k 10,000 People - Human Pose Recognition Data CIFAR-10 STL-10

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	ResNet50	ImageNet Top-1 Accuracy	73.6	—	Unverified
2	ResNet50	ImageNet Top-1 Accuracy	73	—	Unverified
3	ResNet50	ImageNet Top-1 Accuracy	71.1	—	Unverified
4	ResNet50	ImageNet Top-1 Accuracy	69.3	—	Unverified
5	ResNet50 (v2)	ImageNet Top-1 Accuracy	67.6	—	Unverified
6	ResNet50 (v2)	ImageNet Top-1 Accuracy	63.8	—	Unverified
7	ResNet50	ImageNet Top-1 Accuracy	63.6	—	Unverified
8	ResNet50	ImageNet Top-1 Accuracy	61.5	—	Unverified
9	ResNet50	ImageNet Top-1 Accuracy	61.5	—	Unverified
10	ResNet50 (4×)	ImageNet Top-1 Accuracy	61.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	1	0..5sec	1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	IPCL (ResNet18)	Accuracy (Top-1)	84.77	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	IPCL (ResNet18)	Accuracy (Top-1)	85.55	—	Unverified