1 code implementation • 6 Apr 2023 • Kang Chen, Tao Han, Junchao Gong, Lei Bai, Fenghua Ling, Jing-Jia Luo, Xi Chen, Leiming Ma, Tianning Zhang, Rui Su, Yuanzheng Ci, Bin Li, Xiaokang Yang, Wanli Ouyang
We present FengWu, an advanced data-driven global medium-range weather forecast system based on Artificial Intelligence (AI).
1 code implementation • CVPR 2023 • Shixiang Tang, Cheng Chen, Qingsong Xie, Meilin Chen, Yizhou Wang, Yuanzheng Ci, Lei Bai, Feng Zhu, Haiyang Yang, Li Yi, Rui Zhao, Wanli Ouyang
Specifically, we propose a \textbf{HumanBench} based on existing datasets to comprehensively evaluate on the common ground the generalization abilities of different pretraining methods on 19 datasets from 6 diverse downstream tasks, including person ReID, pose estimation, human parsing, pedestrian attribute recognition, pedestrian detection, and crowd counting.
Ranked #1 on Pedestrian Attribute Recognition on PA-100K (using extra training data)
1 code implementation • CVPR 2023 • Yuanzheng Ci, Yizhou Wang, Meilin Chen, Shixiang Tang, Lei Bai, Feng Zhu, Rui Zhao, Fengwei Yu, Donglian Qi, Wanli Ouyang
When adapted to a specific task, UniHCP achieves new SOTAs on a wide range of human-centric tasks, e. g., 69. 8 mIoU on CIHP for human parsing, 86. 18 mA on PA-100K for attribute prediction, 90. 3 mAP on Market1501 for ReID, and 85. 8 JI on CrowdHuman for pedestrian detection, performing better than specialized models tailored for each task.
Ranked #1 on Pose Estimation on MS-COCO
1 code implementation • 17 Jul 2022 • Yuanzheng Ci, Chen Lin, Lei Bai, Wanli Ouyang
Contrastive-based self-supervised learning methods achieved great success in recent years.
1 code implementation • ICCV 2021 • Yuanzheng Ci, Chen Lin, Ming Sun, BoYu Chen, Hongwen Zhang, Wanli Ouyang
The automation of neural architecture design has been a coveted alternative to human experts.
2 code implementations • 9 Aug 2018 • Yuanzheng Ci, Xinzhu Ma, Zhihui Wang, Haojie Li, Zhongxuan Luo
Scribble colors based line art colorization is a challenging computer vision problem since neither greyscale values nor semantic information is presented in line arts, and the lack of authentic illustration-line art training pairs also increases difficulty of model generalization.