Contrastive Learning

Contrastive learning is a self-supervised machine learning technique that aims to learn robust data representations by contrasting similar and dissimilar data points. Current research focuses on applying contrastive learning to diverse modalities, including images, audio, text, and time-series data, often within multimodal frameworks and using architectures like MoCo and SimCLR, and exploring its application in various tasks such as object detection, speaker verification, and image dehazing. This approach is significant because it allows for effective learning from unlabeled or weakly labeled data, improving model generalization and performance across numerous applications, particularly in scenarios with limited annotated data or significant domain shifts.

Papers

July 27, 2023

Self-Contrastive Graph Diffusion Network
Yixian Ma, Kun Zhan
Contrastive Learning Graph Neural Contrastive Method Contrastive Objective Laplacian Learning
GenCo: An Auxiliary Generator from Contrastive Learning for Enhanced Few-Shot Learning in Remote Sensing
Jing Wu, Naira Hovakimyan, Jennifer Hobbs
LeArning Abstract Contrastive Learning Shot Learning Remote Sensing Synchronous Generator Land Cover Classification

July 26, 2023

Towards multi-modal anatomical landmark detection for ultrasound-guided brain tumor resection with contrastive learning
Soorena Salari, Amirhossein Rasoulian, Hassan Rivaz, Yiming Xiao
Contrastive Learning Anatomical Landmark Detection Ultrasound Registration Ultrasound Guided
G2L: Semantically Aligned and Uniform Video Grounding via Geodesic and Game Theory
Hongxiang Li, Meng Cao, Xuxin Cheng, Yaowei Li, Zhihong Zhu, Yuexian Zou
Contrastive Learning Video Representation Game Theory Generalized Geodesic Video Grounding Ground a Video
Entropy Neural Estimation for Graph Contrastive Learning
Yixuan Ma, Xiaolin Zhang, Peng Zhang, Kun Zhan
Contrastive Learning Loss Function Dimensional Embeddings Graph Encoder Pairwise Alignment Entropy Neural
Improving Semi-Supervised Semantic Segmentation with Dual-Level Siamese Structure Network
Zhibo Tain, Xiaolin Zhang, Peng Zhang, Kun Zhan
Contrastive Learning Semantic Segmentation Semi Supervised Siamese Network Semi Supervised Semantic Segmentation Pseudo Label Selection

July 24, 2023

General-Purpose Multi-Modal OOD Detection Framework
Viet Duong, Qiong Wu, Zhengyi Zhou, Eric Zavesky, Jiahe Chen, Xiangzhou Liu, Wen-Ling Hsu, Huajie Shao
Contrastive Learning Distribution Detection Distribution Sample
MARIO: Model Agnostic Recipe for Improving OOD Generalization of Graph Contrastive Learning
Yun Zhu, Haizhou Shi, Zhenshuo Zhang, Siliang Tang
Contrastive Learning Distribution Generalization Generalizable Representation Unsupervised Graph Recipe Dataset Robust Graph Representation
Towards a Visual-Language Foundation Model for Computational Pathology
Ming Y. Lu, Bowen Chen, Drew F. K. Williamson, Richard J. Chen, Ivy Liang, Tong Ding, Guillaume Jaume, Igor Odintsov, Andrew Zhang, Long Phi Le, Georg Gerber, Anil V Parwani, Faisal Mahmood
Contrastive Learning Digital Pathology Histopathological Image Computational Pathology Histopathology Image Vision Language Foundation Model
CLIP-KD: An Empirical Study of CLIP Model Distillation
Chuanguang Yang, Zhulin An, Libo Huang, Junyu Bi, Xinqiang Yu, Han Yang, Boyu Diao, Yongjun Xu
Contrastive Learning Vision Language Empirical Study Contrastive Language Image
PRIOR: Prototype Representation Joint Learning from Medical Images and Reports
Pujin Cheng, Li Lin, Junyan Lyu, Yijin Huang, Wenhan Luo, Xiaoying Tang
Contrastive Learning Fine Grained Medical Image Vision Language Reward Model Multi Modal Alignment Bethesda Report
Homophily-Driven Sanitation View for Robust Graph Contrastive Learning
Yulin Zhu, Xing Ai, Yevgeniy Vorobeychik, Kai Zhou
Contrastive Learning Adversarial Robustness Graph Contrastive Learning Structural Attack Homophily Level

July 22, 2023

Hallucination Improves the Performance of Unsupervised Visual Representation Learning
Jing Wu, Jennifer Hobbs, Naira Hovakimyan
Contrastive Learning System Performance Content Hallucination Contrastive Example Unsupervised Visual Representation Learning Confidence Aware Contrastive
Extracting Molecular Properties from Natural Language with Multimodal Contrastive Learning
Romain Lacombe, Andrew Gaut, Jeff He, David Lüdeke, Kateryna Pistunova
Contrastive Learning Natural Language Molecular Graph Molecular Property Molecular Property Prediction Task
Contrastive Self-Supervised Learning Based Approach for Patient Similarity: A Case Study on Atrial Fibrillation Detection from PPG Signal
Subangkar Karmaker Shanto, Shoumik Saha, Atif Hasan Rahman, Mohammad Mehedy Masud, Mohammed Eunus Ali
Contrastive Learning Self Supervised Case Study PPG Signal Physiological Time Series Data Similar Embeddings Atrial Fibrillation Detection Patient Similarity

July 20, 2023

Identical and Fraternal Twins: Fine-Grained Semantic Contrastive Learning of Sentence Representations
Qingfa Xiao, Shuangyin Li, Lei Chen
Contrastive Learning Sentence Representation Semantic Feature Semantic Textual Similarity Contrastive Objective Identical Twin Fine Grained Contrastive Learning Innate Document Segment Structure
Learning Discriminative Visual-Text Representation for Polyp Re-Identification
Suncheng Xiang, Cang Liu, Sijia Du, Dahong Qian
Contrastive Learning Polyp Segmentation Visual Representation Learning Visual Language Video Polyp Segmentation

July 19, 2023

Density-invariant Features for Distant Point Cloud Registration
Quan Liu, Hongzi Zhu, Yunsong Zhou, Hongyang Li, Shan Chang, Minyi Guo
Contrastive Learning Point Cloud Density Invariant
Source-Free Domain Adaptation for Medical Image Segmentation via Prototype-Anchored Feature Alignment and Contrastive Learning
Qinji Yu, Nan Xi, Junsong Yuan, Ziyu Zhou, Kang Dang, Xiaowei Ding
Contrastive Learning Domain Adaptation Medical Image Segmentation Unsupervised Domain Adaptation Source Free Domain Adaptation Cross Modality Prototype Alignment
Space Engage: Collaborative Space Supervision for Contrastive-based Semi-Supervised Semantic Segmentation
Changqi Wang, Haoyu Xie, Yuhui Yuan, Chong Fu, Xiangyu Yue
Contrastive Learning Latent Space Segmentation Model Semi Supervised Semantic Segmentation Perspective Supervision

Contrastive Learning

Papers

Self-Contrastive Graph Diffusion Network

GenCo: An Auxiliary Generator from Contrastive Learning for Enhanced Few-Shot Learning in Remote Sensing

Towards multi-modal anatomical landmark detection for ultrasound-guided brain tumor resection with contrastive learning

G2L: Semantically Aligned and Uniform Video Grounding via Geodesic and Game Theory

Entropy Neural Estimation for Graph Contrastive Learning

Improving Semi-Supervised Semantic Segmentation with Dual-Level Siamese Structure Network

General-Purpose Multi-Modal OOD Detection Framework

MARIO: Model Agnostic Recipe for Improving OOD Generalization of Graph Contrastive Learning

Towards a Visual-Language Foundation Model for Computational Pathology

CLIP-KD: An Empirical Study of CLIP Model Distillation

PRIOR: Prototype Representation Joint Learning from Medical Images and Reports

Homophily-Driven Sanitation View for Robust Graph Contrastive Learning

Hallucination Improves the Performance of Unsupervised Visual Representation Learning

Extracting Molecular Properties from Natural Language with Multimodal Contrastive Learning

Contrastive Self-Supervised Learning Based Approach for Patient Similarity: A Case Study on Atrial Fibrillation Detection from PPG Signal

Identical and Fraternal Twins: Fine-Grained Semantic Contrastive Learning of Sentence Representations

Learning Discriminative Visual-Text Representation for Polyp Re-Identification

Density-invariant Features for Distant Point Cloud Registration

Source-Free Domain Adaptation for Medical Image Segmentation via Prototype-Anchored Feature Alignment and Contrastive Learning

Space Engage: Collaborative Space Supervision for Contrastive-based Semi-Supervised Semantic Segmentation