Imagen de Portada

CADet: Fully Self-Supervised Out-Of-Distribution Detection With Contrastive Learning

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Guille-Escuret, Charles, Rodriguez, Pau, Vazquez, David, Mitliagkas, Ioannis, Monteiro, Joao
Formato:	Preprint
Publicado:	2022
Materias:	Machine Learning Computer Vision and Pattern Recognition
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Expecting The Unexpected: Towards Broad Out-Of-Distribution Detection
por: Guille-Escuret, Charles, et al.
Publicado: (2023)

A Study of Condition Numbers for First-Order Optimization
por: Guille-Escuret, Charles, et al.
Publicado: (2020)

BootOOD: Self-Supervised Out-of-Distribution Detection via Synthetic Sample Exposure under Neural Collapse
por: Wang, Yuanchao, et al.
Publicado: (2025)

Dynamically Scaled Temperature in Self-Supervised Contrastive Learning
por: Manna, Siladittya, et al.
Publicado: (2023)

ProSub: Probabilistic Open-Set Semi-Supervised Learning with Subspace-Based Out-of-Distribution Detection
por: Wallin, Erik, et al.
Publicado: (2024)

Learning with Mixture of Prototypes for Out-of-Distribution Detection
por: Lu, Haodong, et al.
Publicado: (2024)

Variational Self-Supervised Contrastive Learning Using Beta Divergence
por: Yavuz, Mehmet Can, et al.
Publicado: (2023)

Gradient Descent Is Optimal Under Lower Restricted Secant Inequality And Upper Error Bound
por: Guille-Escuret, Charles, et al.
Publicado: (2022)

Variational Supervised Contrastive Learning
por: Wang, Ziwen, et al.
Publicado: (2025)

Out-of-Distribution Detection & Applications With Ablated Learned Temperature Energy
por: LeVine, Will, et al.
Publicado: (2024)

MIO : Mutual Information Optimization using Self-Supervised Binary Contrastive Learning
por: Manna, Siladittya, et al.
Publicado: (2021)

Activation Subspaces for Out-of-Distribution Detection
por: Zöngür, Barış, et al.
Publicado: (2025)

Out-of-Distribution Detection with Relative Angles
por: Demirel, Berker, et al.
Publicado: (2024)

Gradient-Regularized Out-of-Distribution Detection
por: Sharifi, Sina, et al.
Publicado: (2024)

Out-Of-Distribution Detection with Diversification (Provably)
por: Yao, Haiyun, et al.
Publicado: (2024)

Enhancing Semi-Supervised Multi-View Graph Convolutional Networks via Supervised Contrastive Learning and Self-Training
por: Xiao, Huaiyuan, et al.
Publicado: (2025)

Long-Tailed Out-of-Distribution Detection with Refined Separate Class Learning
por: Feng, Shuai, et al.
Publicado: (2025)

OpenMIBOOD: Open Medical Imaging Benchmarks for Out-Of-Distribution Detection
por: Gutbrod, Max, et al.
Publicado: (2025)

Vendi Novelty Scores for Out-of-Distribution Detection
por: Pasarkar, Amey P., et al.
Publicado: (2026)

Unsupervised Contrastive Learning Using Out-Of-Distribution Data for Long-Tailed Dataset
por: Hoang, Cuong Manh, et al.
Publicado: (2025)

Self-Supervised Detection of Perfect and Partial Input-Dependent Symmetries
por: Urbano, Alonso, et al.
Publicado: (2023)

Self-Calibrated Tuning of Vision-Language Models for Out-of-Distribution Detection
por: Yu, Geng, et al.
Publicado: (2024)

Self-Supervised Contrastive Learning for Videos using Differentiable Local Alignment
por: Oei, Keyne, et al.
Publicado: (2024)

On the Detection of Anomalous or Out-Of-Distribution Data in Vision Models Using Statistical Techniques
por: O'Mahony, Laura, et al.
Publicado: (2024)

FlowCon: Out-of-Distribution Detection using Flow-Based Contrastive Learning
por: Aathreya, Saandeep, et al.
Publicado: (2024)

Learning Multi-Manifold Embedding for Out-Of-Distribution Detection
por: Li, Jeng-Lin, et al.
Publicado: (2024)

Visually Robust Adversarial Imitation Learning from Videos with Contrastive Learning
por: Giammarino, Vittorio, et al.
Publicado: (2024)

Network Inversion for Uncertainty-Aware Out-of-Distribution Detection
por: Suhail, Pirzada, et al.
Publicado: (2025)

Toward a Realistic Benchmark for Out-of-Distribution Detection
por: Recalcati, Pietro, et al.
Publicado: (2024)

Energy-based Hopfield Boosting for Out-of-Distribution Detection
por: Hofmann, Claus, et al.
Publicado: (2024)

Iterative Deployment Exposure for Unsupervised Out-of-Distribution Detection
por: Doorenbos, Lars, et al.
Publicado: (2024)

Are We Ready for Out-of-Distribution Detection in Digital Pathology?
por: Oh, Ji-Hun, et al.
Publicado: (2024)

Hypercone Assisted Contour Generation for Out-of-Distribution Detection
por: Vapsi, Annita, et al.
Publicado: (2025)

NODI: Out-Of-Distribution Detection with Noise from Diffusion
por: Zhou, Jingqiu, et al.
Publicado: (2024)

Shaping Parameter Contribution Patterns for Out-of-Distribution Detection
por: Xu, Haonan, et al.
Publicado: (2026)

Self-Tuning Self-Supervised Image Anomaly Detection
por: Yoo, Jaemin, et al.
Publicado: (2023)

From Conformal Predictions to Confidence Regions
por: Guille-Escuret, Charles, et al.
Publicado: (2024)

CONSULT: Contrastive Self-Supervised Learning for Few-shot Tumor Detection
por: Chin, Sin Chee, et al.
Publicado: (2024)

Leveraging Self-Supervised Instance Contrastive Learning for Radar Object Detection
por: Decourt, Colin, et al.
Publicado: (2024)

Detecting Out-of-Distribution Samples via Conditional Distribution Entropy with Optimal Transport
por: Feng, Chuanwen, et al.
Publicado: (2024)