Danfei Xu

I am a Ph.D. student in CS at Stanford University. My advisors are Fei-Fei Li and Silvio Savarese who co-lead the Stanford Vision and Learning Lab. My research focuses on compositional and generalizable structures in robotics and vision.

Prior to joining Stanford, I received my B.S. from Columbia University (2015). I've worked/interned at DeepMind UK (2019), ZOOX (2017), Autodesk Research (2016), CMU RI (2014), and Columbia Robotics Lab (2013-2015).

Email  /  Google Scholar  /  CV (Jan 2019)  /  Github  /  Twitter

News
  • [Sep 2019] Regression Planning Networks accepted at NeurIPS 2019. Paper and code coming soon.
  • [June 2019] Neural Task Graphs (oral) and DenseFusion presented at CVPR 2019
  • [Jan 2019] We have released the code and arXiv preprint for our DenseFusion project.
Research
Regression Planning Networks
Danfei Xu, Roberto Martin-Martin, De-An Huang, Yuke Zhu, Silvio Savarese, Li Fei-Fei
NeurIPS, 2019

Code coming soon.

A flexible neural network architecture for learning to plan from video demonstrations.

Continuous Relaxation of Symbolic Planner for One-Shot Imitation Learning
De-An Huang, Danfei Xu, Yuke Zhu, Silvio Savarese, Li Fei-Fei, Juan Carlos Niebles
IROS , 2019

One-shot imitation learning via hybrid neural-symbolic planning.

Situational Fusion of Visual Representation for Visual Navigation
William B. Shen, Danfei Xu, Yuke Zhu, Leonidas Guibas, Li Fei-Fei, Silvio Savarese
ICCV , 2019

Learning generalizable navigation policy from mid-level visual representations.

DenseFusion: 6D Object Pose Estimation by Iterative Dense Fusion
Chen Wang, Danfei Xu, Yuke Zhu, Roberto Martin-Martin, Cewu Lu, Li Fei-Fei, Silvio Savarese
CVPR, 2019

[website] [video] [code]

Dense RGB-depth sensor fusion for 6D object pose estimation.

Neural Task Graphs: Generalizing to Unseen Tasks from a Single Video Demonstration
De-An Huang*, Suraj Nair*, Danfei Xu*, Yuke Zhu, Animesh Garg, Li Fei-Fei, Silvio Savarese, Juan Carlos Niebles
CVPR, 2019 (Oral)

Generate executable task graphs from video demonstrations.

Neural Task Programming: Learning to Generalize Across Hierarchical Tasks
Danfei Xu*, Suraj Nair*, Yuke Zhu, Julian Gao, Animesh Garg, Li Fei-Fei, Silvio Savarese
ICRA, 2018

[website] [video] [Two Minute Papers]

Neural Task Programming (NTP) is a meta-learning framework that learns to generate robot-executable neural programs from task demonstration video.

PointFusion: Deep Sensor Fusion for 3D Bounding Box Estimation
Danfei Xu, Ashesh Jain, Dragomir Anguelov
CVPR, 2018

End-to-end 3D Bounding Box Estimation via sensor fusion.

Scene Graph Generation by Iterative Message Passing
Danfei Xu, Yuke Zhu, Christopher B. Choy, Li Fei-Fei
CVPR, 2017

[website] [code]

We propose an end-to-end model that jointly infers object category, location, and relationships. The model learns to iteratively improve its prediction by passing messages on a scene graph.

3D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstruction
Christopher B. Choy, Danfei Xu*, JunYoung Gwak*, Silvio Savarese
ECCV, 2016

[website] [code]

We propose an end-to-end 3D reconstruction model that unifies single- and multi-view reconstruction.

Model-Driven Feed-Forward Prediction for Manipulation of Deformable Objects
Yinxiao Li , Yan Wang , Yonghao Yue , Danfei Xu, Michael Case , Shih-Fu Chang , Eitan Grinspun , Peter K. Allen
IEEE TASE, 2016

[website]

Deformable object manipulation with an application of personal assitive robot.

This is the journal paper of our "laundry robot" series:
ICRA 2015
IROS 2015
ICRA 2016

Topometric localization on a road network
Danfei Xu, Hernan Badino, Daniel Huber
IROS, 2015

Vision-based localization on a probabilistic road network.

Tactile identification of objects using Bayesian exploration
Danfei Xu, Gerald E. Loeb, Jeremy Fishel
ICRA, 2013

Object classification using multi-modal tactile sensing.


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