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Out-of-Distribution (OOD) detection is critical for ensuring the reliability of machine learning models in safety-critical applications such as autonomous driving and medical diagnosis.
A duality based approach for realtime tv-l 1 optical flow
Christopher Zach, Thomas Pock, and Horst Bischof · 2007
Earlier work this paper cites.
Hmdb: a large video database for human motion recognition
Hildegard Kuehne, Hueihan Jhuang, Estíbaliz Garrote, Tomaso Poggio, and Thomas Serre · 2011
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Ucf101: A dataset of 101 human actions classes from videos in the wild
Khurram Soomro, Amir Roshan Zamir, and Mubarak Shah · 2012
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A baseline for detecting misclassified and out-of-distribution examples in neural networks
Dan Hendrycks and Kevin Gimpel · 2017
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The kinetics human action video dataset
Will Kay, Joao Carreira, Karen Simonyan, Brian Zhang, Chloe Hillier, Sudheendra Vijayanarasimhan, Fabio Viola, Tim Green, Trevor Back, Paul Natsev, et al · 2017
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A survey on homomorphic encryption schemes: Theory and implementation
Abbas Acar, Hidayet Aksu, A Selcuk Uluagac, and Mauro Conti · 2018
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Scaling egocentric vision: The epic-kitchens dataset
Dima Damen, Hazel Doughty, Giovanni Maria Farinella, Sanja Fidler, Antonino Furnari, Evangelos Kazakos, Davide Moltisanti, Jonathan Munro, Toby Perrett, Will Price, and Michael Wray · 2018
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A simple unified framework for detecting out-of-distribution samples and adversarial attacks
Kimin Lee, Kibok Lee, Honglak Lee, and Jinwoo Shin · 2018
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Deep continuous fusion for multi-sensor 3d object detection
Ming Liang, Bin Yang, Shenlong Wang, and Raquel Urtasun · 2018
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Explanation of machine learning models using improved shapley additive explanation
Yasunobu Nohara, Koutarou Matsumoto, Hidehisa Soejima, and Naoki Nakashima · 2019
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Energy-based out-of-distribution detection
Weitang Liu, Xiaoyun Wang, John D Owens, and Yixuan Li · 2020
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Multi-modal Domain Adaptation for Fine-grained Action Recognition
Jonathan Munro and Dima Damen · 2020
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Explaining anomalies detected by autoencoders using shapley additive explanations
Liat Antwarg, Ronnie Mindlin Miller, Bracha Shapira, and Lior Rokach · 2021
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Meta-learning in neural networks: A survey
Timothy Hospedales, Antreas Antoniou, Paul Micaelli, and Amos Storkey · 2021
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React: Out-of-distribution detection with rectified activations
Yiyou Sun, Chuan Guo, and Yixuan Li · 2021
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Device-cloud collaborative learning for recommendation
Jiangchao Yao, Feng Wang, Kunyang Jia, Bo Han, Jingren Zhou, and Hongxia Yang · 2021
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Fedavg with fine tuning: Local updates lead to representation learning
Liam Collins, Hamed Hassani, Aryan Mokhtari, and Sanjay Shakkottai · 2022
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Extremely simple activation shaping for out-of-distribution detection
Andrija Djurisic, Nebojsa Bozanic, Arjun Ashok, and Rosanne Liu · 2022
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Superfusion: Multilevel lidar-camera fusion for long-range hd map generation
SimMMDG: A simple and effective framework for multi-modal domain generalization
Hao Dong, Ismail Nejjar, Han Sun, Eleni Chatzi, and Olga Fink · 2023
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Denoising diffusion models for out-of-distribution detection
Mark S. Graham, Walter H. L. Pinaya, Petru-Daniel Tudosiu, Parashkev Nachev, Sebastien Ourselin, and M. Jorge Cardoso · 2023
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Gen: Pushing the limits of softmax-based out-of-distribution detection
Xixi Liu, Yaroslava Lochman, and Christopher Zach · 2023
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An uncertainty-aware deep learning model for reliable detection of steel wire rope defects
Wenting Yi, Wai Kit Chan, Hiu Hung Lee, Steven T Boles, and Xiaoge Zhang · 2023
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Id-like prompt learning for few-shot out-of-distribution detection
Yichen Bai, Zongbo Han, Bing Cao, Xiaoheng Jiang, Qinghua Hu, and Changqing Zhang · 2024
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Hao Dong, Xianjing Zhang, Jintao Xu, Rui Ai, Weihao Gu, Huimin Lu, Juho Kannala, and Xieyuanli Chen · 2022
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Unknown-aware object detection: Learning what you don’t know from videos in the wild
Xuefeng Du, Xin Wang, Gabriel Gozum, and Yixuan Li · 2022
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Hypernetworks
David Ha, Andrew M Dai, and Quoc V Le · 2022
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Scaling out-of-distribution detection for real-world settings
Dan Hendrycks, Steven Basart, Mantas Mazeika, Andy Zou, Joe Kwon, Mohammadreza Mostajabi, Jacob Steinhardt, and Dawn Song · 2022
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Improving calibration and out-of-distribution detection in deep models for medical image segmentation
Davood Karimi and Ali Gholipour · 2022
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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, et al · 2022
Cited alongside, same era.
Training auxiliary prototypical classifiers for explainable anomaly detection in medical image segmentation
Wonwoo Cho, Jeonghoon Park, and Jaegul Choo · 2023
Cited alongside, same era.
Hao Dong, Yue Zhao, Eleni Chatzi, and Olga Fink · 2024
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Artificial intelligence-aided digital twin design: A systematic review
Nan Hao, Yuangang Li, Kecheng Liu, Songtao Liu, Yingzhou Lu, Bohao Xu, Chenhao Li, Jintai Chen, Ling Yue, Tianfan Fu, et al · 2024
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Split learning in 6g edge networks
Zheng Lin, Guanqiao Qu, Xianhao Chen, and Kaibin Huang · 2024
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Metaood: Automatic selection of ood detection models
Yuehan Qin, Yichi Zhang, Yi Nian, Xueying Ding, and Yue Zhao · 2024
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Model optimization techniques in personalized federated learning: A survey
Fahad Sabah, Yuwen Chen, Zhen Yang, Muhammad Azam, Nadeem Ahmad, and Raheem Sarwar · 2024
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Lego-learn: Label-efficient graph open-set learning
Haoyan Xu, Kay Liu, Zhengtao Yao, Philip S Yu, Kaize Ding, and Yue Zhao · 2024
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Backpropagation-free multi-modal on-device model adaptation via cloud-device collaboration
Wei Ji, Li Li, Zheqi Lv, Wenqiao Zhang, Mengze Li, Zhen Wan, Wenqiang Lei, and Roger Zimmermann · 2025
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