Knowledge Commons of Institute of Automation,CAS
Unified Entropy Optimization for Open-Set Test-Time Adaptation | |
Zhengqing Gao1,2![]() ![]() ![]() | |
2024 | |
会议名称 | IEEE/CVF Computer Vision and Pattern Recognition Conference |
会议日期 | June 17-21, 2024 |
会议地点 | Seattle WA, USA |
出版者 | IEEE/CVF |
摘要 | Test-time adaptation (TTA) aims at adapting a model pre-trained on the labeled source domain to the unlabeled target domain. Existing methods usually focus on improving TTA performance under covariate shifts, while neglecting semantic shifts. In this paper, we delve into a realistic open-set TTA setting where the target domain may contain samples from unknown classes. Many state-of-the-art closed-set TTA methods perform poorly when applied to open-set scenarios, which can be attributed to the inaccurate estimation of data distribution and model confidence. To address these issues, we propose a simple but effective framework called unified entropy optimization (UniEnt), which is capable of simultaneously adapting to covariate-shifted in-distribution (csID) data and detecting covariate-shifted out-of-distribution (csOOD) data. Specifically, UniEnt first mines pseudo-csID and pseudo-csOOD samples from test data, followed by entropy minimization on the pseudo-csID data and entropy maximization on the pseudo-csOOD data. Furthermore, we introduce UniEnt+ to alleviate the noise caused by hard data partition leveraging sample-level confidence. Extensive experiments on CIFAR benchmarks and Tiny-ImageNet-C show the superiority of our framework. The code is available at https://github.com/gaozhengqing/UniEnt. |
七大方向——子方向分类 | 模式识别基础 |
国重实验室规划方向分类 | 人工智能基础前沿理论 |
是否有论文关联数据集需要存交 | 否 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/57397 |
专题 | 多模态人工智能系统全国重点实验室_模式分析与学习 |
通讯作者 | Xu-Yao Zhang |
作者单位 | 1.MAIS, Institute of Automation, Chinese Academy of Sciences 2.School of Artificial Intelligence, University of Chinese Academy of Sciences |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Zhengqing Gao,Xu-Yao Zhang,Cheng-Lin Liu. Unified Entropy Optimization for Open-Set Test-Time Adaptation[C]:IEEE/CVF,2024. |
条目包含的文件 | 下载所有文件 | |||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
2404.06065.pdf(6643KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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