1 citations · 2 across the 10 of their papers we have counts for
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Long-Tailed Out-of-Distribution Detection via Normalized Outlier Distribution Adaptation
Wenjun Miao, Guansong Pang, Jin Zheng +1
One key challenge in Out-of-Distribution (OOD) detection is the absence of ground-truth OOD samples during training. One principled approach to address this issue is to use samples…
OpenCIL: Benchmarking Out-of-Distribution Detection in Class-Incremental Learning
Wenjun Miao, Guansong Pang, Trong-Tung Nguyen +3
Class incremental learning (CIL) aims to learn a model that can not only incrementally accommodate new classes, but also maintain the learned knowledge of old classes. Out-of-distr…
Zero-Shot Out-of-Distribution Detection with Outlier Label Exposure
Choubo Ding, Guansong Pang
As vision-language models like CLIP are widely applied to zero-shot tasks and gain remarkable performance on in-distribution (ID) data, detecting and rejecting out-of-distribution…
Learning Transferable Negative Prompts for Out-of-Distribution Detection
Tianqi Li, Guansong Pang, Xiao Bai +2
Existing prompt learning methods have shown certain capabilities in Out-of-Distribution (OOD) detection, but the lack of OOD images in the target dataset in their training can lead…