Xingyu Liu

Ph.D. Candidate
Stanford University


I have joined the Robotics Institute of Carnegie Mellon University as a Postdoctoral Fellow. This webpage will not be updated. Please visit my up-to-date homepage.

Welcome to my home page! I received my Ph.D. from Stanford University where I was advised by Professor Jeannette Bohg in Interactive Perception and Robot Learning Lab (IPRL) and Stanford AI Lab (SAIL). My research interest is in the broad disciplines related to artificial intelligence, particularly in computer vision, deep learning and their applications to robotic manipulation and autonomous driving. Check out my Ph.D. thesis here.

Prior to coming to Stanford, I received my Bachelor's degree from Tsinghua University. I was an undergraduate exchange student at the ECE Department of University of Toronto. I previously interned at Google Brain Robotics, Adobe Research, Amazon A9, NVIDIA and Microsoft Research Asia.

Education

Ph.D. in Electrical Engineering, 2015 - 2019
M.S. in Computer Science, 2016 - 2019
B.Eng. in Microelectronics with Honors, 2011 - 2015
Exchange Student, Electrical and Computer Engineering, 2013

Publications

KeyPose: Multi-view 3D Labeling and Keypoint Estimation for Transparent Objects

Xingyu Liu, Rico Jonschkowski, Anelia Angelova, Kurt Konolige
CVPR 2020
[PDF][Code coming soon][Data coming soon][Bibtex]

MeteorNet: Deep Learning on Dynamic 3D Point Cloud Sequences

Xingyu Liu, Mengyuan Yan, Jeannette Bohg
ICCV 2019 (Oral presentation, acceptance rate: 4.3%)
[PDF][Code][Oral][Project][Bibtex]

Learning Video Representations from Correspondence Proposals

Xingyu Liu, Joon-Young Lee, Hailin Jin
CVPR 2019 (Oral presentation, acceptance rate: 5.6%)
[PDF][Code][Oral][Bibtex]

FlowNet3D: Learning Scene Flow in 3D Point Clouds

Xingyu Liu*, Charles R. Qi*, Leonidas J. Guibas
CVPR 2019
[PDF][Code][Bibtex]

Efficient Sparse-Winograd Convolutional Neural Networks

Xingyu Liu, Jeff Pool, Song Han, William J. Dally
[PDF][Code][Bibtex]

EIE: Efficient Inference Engine on Compressed Deep Neural Network

Song Han, Xingyu Liu, Huizi Mao, Jing Pu, Ardavan Pedram, Mark A. Horowitz, William J. Dally
ISCA 2016
[PDF][Slides][Bibtex]

RadixBoost: A Hardware Acceleration Structure for Scalable Radix Sort on Graphic Processors

Xingyu Liu, Shikai Li, Kuan Fang, Yufei Ni, Zonghui Li, Yangdong Deng
ISCAS 2015
[PDF][Bibtex]

FastTree: A Hardware KD-tree Construction Acceleration Engine for Real-time Ray Tracing

Xingyu Liu, Yangdong Deng, Yufei Ni, Zonghui Li
DATE 2015
[PDF][Bibtex]

Industry Experience

Research Intern, Jun 2019 - Dec 2019
Research Intern, Jun 2018 - Sep 2018
Research Intern, Jun 2017 - Sep 2017

NVIDIA

Compute Architecture Team, Santa Clara, CA
Research Intern, Jun 2016 - Sep 2016

Teaching

Teaching Assistant, Sep 2019 - Dec 2019


Teaching Assistant, Jan 2018 - Mar 2018

Teaching Assistant, Sep 2017 - Dec 2017

Service

Conference Reviewer: CVPR, ICCV, ECCV, NeurIPS, ICML, AAAI
Journal Reviewer: TVLSI