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20212024
most citedConstrained Adaptive Projection with Pretrained Features for Anomaly Detection

1 citations · 2 across the 5 of their papers we have counts for

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5 papers

cs.CV2024

Unsupervised Anomaly Detection via Masked Diffusion Posterior Sampling

Di Wu, Shicai Fan, Xue Zhou +4

Reconstruction-based methods have been commonly used for unsupervised anomaly detection, in which a normal image is reconstructed and compared with the given test image to detect a…

cs.CV20231 cited

Variational Probabilistic Fusion Network for RGB-T Semantic Segmentation

Baihong Lin, Zengrong Lin, Yulan Guo +3

RGB-T semantic segmentation has been widely adopted to handle hard scenes with poor lighting conditions by fusing different modality features of RGB and thermal images. Existing me…

cs.CV2023

Cluster-aware Contrastive Learning for Unsupervised Out-of-distribution Detection

Menglong Chen, Xingtai Gui, Shicai Fan

Unsupervised out-of-distribution (OOD) Detection aims to separate the samples falling outside the distribution of training data without label information. Among numerous branches,…

cs.IR2022

SPR:Supervised Personalized Ranking Based on Prior Knowledge for Recommendation

Chun Yang, Shicai Fan

The goal of a recommendation system is to model the relevance between each user and each item through the user-item interaction history, so that maximize the positive samples score…

cs.CV20211 cited

Constrained Adaptive Projection with Pretrained Features for Anomaly Detection

Xingtai Gui, Di Wu, Yang Chang +1

Anomaly detection aims to separate anomalies from normal samples, and the pretrained network is promising for anomaly detection. However, adapting the pretrained features would be…