Classifier-Head Informed Feature Masking and Prototype-Based Logit Smoothing for Out-of-Distribution Detection
Author:
Affiliation:
1. School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China
2. Department of Computer Science and Engineering, University of California at San Diego, La Jolla, CA, USA
Funder
Major Key Project of Peng Cheng Laboratory
NSFC
Guangdong Excellent Youth Team Program
National Key Research and Development Program of China
Guangdong NSF
Guangdong Province Key Laboratory of Computational Science, Sun Yat-sen University
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/76/10582818/10415468.pdf?arnumber=10415468
Reference60 articles.
1. MOS: Towards Scaling Out-of-distribution Detection for Large Semantic Space
2. A baseline for detecting misclassified and out-of-distribution examples in neural networks;Hendrycks
3. A Survey of Open-World Person Re-Identification
4. Can autonomous vehicles identify, recover from, and adapt to distribution shifts?;Filos
5. Vision-Based Traffic Accident Detection and Anticipation: A Survey
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