I am a last-year undergradutate in School of EECS at Peking University, majoring in Computer Science advised by Prof. Zhanxing Zhu. I have been a research intern at Megvii Inc.(Face++) mentored by Dr. Xiangyu Zhang since March, 2018.
This winter, I will apply for Ph.D.
- Computer vision and deep learning, especially visual recognitions, maniuplating images.
- Efficient learning and inference. Speed up the training of NNs. AutoML, NAS for light-weight NNs.
- Dynamic networks.
- Understanding the relationship between data and current deep models.
[September, 2019] YOPO was accepted by NeurIPS19.
[July, 2019] One paper accepted by ICCV19.
[April, 2019] One paper accepted by ICML19.
[April. 2019] We published a new general detection dataset Objects365, which is designed to spur object detection research with a focus on diverse objects in the Wild.
Objects365: A Large-scale, High-quality Dataset for Object Detection, Shuai Shao*, Zeming Li*, Tianyuan Zhang*, Chao Peng*, Gang Yu, Xiangyu Zhang, Jing Li, Jian Sun. (*equal contribution) ICCV, 2019
You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle. Dinghuai Zhang*, Tianyuan Zhang*,Yiping Lu*, Zhanxing Zhu, Bin Dong. (*equal contribution) [code] 33rd Annual Conference on Neural Information Processing Systems (NeurIPS 2019)
Interpreting Adversarially Trained Convolutional Neural Networks. Tianyuan Zhang, Zhanxing Zhu. [code] International Conference on Machine Learning (ICML), 2019.