Hi, I am Tianyuan Zhang(张天远, pronounced as Tien-Yuen Jahng), a first-year master student in Robotics Institue at Carnegie Mellon University supervised by Prof. Srinivasa Narasimhan. I also worked with Prof. Hang Zhao at Tsinghua University. Previously, I finished my undergraduate in School of EECS at Peking University, majoring in Computer Science advised by Prof. Zhanxing Zhu. I spent two years of my undergraduate life at Megvii Inc.(Face++) as a research intern mentored by Dr. Xiangyu Zhang. Later I joined Microsoft Research Asia as a research intern advised by Dr. Di He.
- Visual recognitaion.
- Visual content creation/editing.
- Autonomous Driving.
- Understanding the prior of current deep learning models.
[November, 2021] We developed an end-to-end multi-camera 3D detection methods with sota performance and simple design, named DETR3D, see our CoRL paper here: DETR3D.
[November, 2020] We developed the first real-time flow based video frame interpolation methods with sota performance, named RIFE, see our demo here: RIFE.
[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.
DETR3D: 3D Object Detection from Multi-view Images via 3D-to-2D Queries, Yue Wang, Vitor Guizilini*, Tianyuan Zhang*, Yilun Wang, Hang Zhao, Justin Solomon. [code] CoRL 2021
RIFE: Real-Time Intermediate Flow Estimation for Video Frame Interpolation, Zhewei Huang, Tianyuan Zhang, Wen Heng, Boxin Shi, Shuchang Zhou. [project page], [code] arXiv preprint
Domain-Aware Dynamic Networks, Tianyuan Zhang, Bichen Wu, Xin Wang, Joseph Gonzalez, Kurt Keutzer. arXiv preprint
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.