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OpenOOD: Benchmarking Generalized Out-of-Distribution Detection
Jingkang Yang · Pengyun Wang · Dejian Zou · Zitang Zhou · Kunyuan Ding · WENXUAN PENG · Haoqi Wang · Guangyao Chen · Bo Li · Yiyou Sun · Xuefeng Du · Kaiyang Zhou · Wayne Zhang · Dan Hendrycks · Yixuan Li · Ziwei Liu

Tue Nov 29 09:00 AM -- 11:00 AM (PST) @ Hall J #1031

Out-of-distribution (OOD) detection is vital to safety-critical machine learning applications and has thus been extensively studied, with a plethora of methods developed in the literature. However, the field currently lacks a unified, strictly formulated, and comprehensive benchmark, which often results in unfair comparisons and inconclusive results. From the problem setting perspective, OOD detection is closely related to neighboring fields including anomaly detection (AD), open set recognition (OSR), and model uncertainty, since methods developed for one domain are often applicable to each other. To help the community to improve the evaluation and advance, we build a unified, well-structured codebase called OpenOOD, which implements over 30 methods developed in relevant fields and provides a comprehensive benchmark under the recently proposed generalized OOD detection framework. With a comprehensive comparison of these methods, we are gratified that the field has progressed significantly over the past few years, where both preprocessing methods and the orthogonal post-hoc methods show strong potential.

Author Information

Jingkang Yang (Nanyang Technological University)
Pengyun Wang (Beijing University of Posts and Telecommunications)
Dejian Zou (Beijing University of Posts and Telecommunications)
Zitang Zhou (Beijing University of Posts and Telecommunications)
Kunyuan Ding (Beijing University of Posts and Telecommunications)
WENXUAN PENG (Nanyang Technological University)
Haoqi Wang (SenseTime)
Guangyao Chen (Peking University)
Bo Li (Nanyang Technological University)
Yiyou Sun (University of Wisconsin, Madison)
Xuefeng Du (UW-Madison)
Kaiyang Zhou (Nanyang Technological University)
Wayne Zhang (SenseTime Research)
Dan Hendrycks (Center for AI Safety)
Yixuan Li (University of Wisconsin-Madison)
Ziwei Liu (Nanyang Technological University)

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