Shaozuo Yu

According to our database, Shaozuo Yu authored at least 10 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

BAL: Balancing Diversity and Novelty for Active Learning.

Jingyao Li, Pengguang Chen, Shaozuo Yu, Shu Liu, Jiaya Jia

IEEE Trans. Pattern Anal. Mach. Intell., May, 2024

MOODv2: Masked Image Modeling for Out-of-Distribution Detection.

Jingyao Li, Pengguang Chen, Shaozuo Yu, Shu Liu, Jiaya Jia

CoRR, 2024

2023

OOD-CV-v2: An extended Benchmark for Robustness to Out-of-Distribution Shifts of Individual Nuisances in Natural Images.

Bingchen Zhao, Jiahao Wang, Wufei Ma, Artur Jesslen, Siwei Yang, Shaozuo Yu, Oliver Zendel, Christian Theobalt, Alan L. Yuille, Adam Kortylewski

CoRR, 2023

Rethinking Out-of-distribution (OOD) Detection: Masked Image Modeling is All You Need.

Jingyao Li, Pengguang Chen, Zexin He, Shaozuo Yu, Shu Liu, Jiaya Jia

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

OOD-CV: A Benchmark for Robustness to Out-of-Distribution Shifts of Individual Nuisances in Natural Images.

Bingchen Zhao, Shaozuo Yu, Wufei Ma, Mingxin Yu, Shenxiao Mei, Angtian Wang, Ju He, Alan L. Yuille, Adam Kortylewski

Proceedings of the Computer Vision - ECCV 2022, 2022

2021

ROBIN : A Benchmark for Robustness to Individual Nuisancesin Real-World Out-of-Distribution Shifts.

Bingchen Zhao, Shaozuo Yu, Wufei Ma, Mingxin Yu, Shenxiao Mei, Angtian Wang, Ju He, Alan L. Yuille, Adam Kortylewski

CoRR, 2021

Rail-5k: a Real-World Dataset for Rail Surface Defects Detection.

Zihao Zhang, Shaozuo Yu, Siwei Yang, Yu Zhou, Bingchen Zhao

CoRR, 2021

Making CNNs Interpretable by Building Dynamic Sequential Decision Forests with Top-down Hierarchy Learning.

Yilin Wang, Shaozuo Yu, Xiaokang Yang, Wei Shen

CoRR, 2021

2020

Reducing the feature divergence of RGB and near-infrared images using Switchable Normalization.

Siwei Yang, Shaozuo Yu, Bingchen Zhao, Yin Wang

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

The 1st Agriculture-Vision Challenge: Methods and Results.

Mang Tik Chiu, Xingqian Xu, Kai Wang, Jennifer A. Hobbs, Naira Hovakimyan, Thomas S. Huang, Honghui Shi, Yunchao Wei, Zilong Huang, Alexander G. Schwing, Robert Brunner, Ivan Dozier, Wyatt Dozier, Karen Ghandilyan, David Wilson, Hyunseong Park, Jun Hee Kim, Sungho Kim, Qinghui Liu, Michael C. Kampffmeyer, Robert Jenssen, Arnt-Børre Salberg, Alexandre Barbosa, Rodrigo G. Trevisan, Bingchen Zhao, Shaozuo Yu, Siwei Yang, Yin Wang, Hao Sheng, Xiao Chen, Jingyi Su, Ram Rajagopal, Andrew Y. Ng, Van Thong Huynh, Soo-Hyung Kim, In Seop Na, Ujjwal Baid, Shubham Innani, Prasad Dutande, Bhakti Baheti, Sanjay N. Talbar, Jianyu Tang

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020