Hao Su

Ph.D Candidate

Geometric Computing Lab and Artificial Intelligence Lab
Dept. of Computer Science
Stanford University, USA

Office: S297 James H. Clark Center
Address: 318 Campus Dr, Stanford, CA 94305
Email: haosu@cs.stanford.edu

bio / google scholar / publication

News

Research Statement

My research interests are computer vision, computer graphics, and machine learning. I particularly focus on joint analysis of 2D images and 3D shapes, that enables information to flow between 2D to 3D domains bidirectionally. Potential applications include 3D reconstruction, robots, virtual/augmented reality, etc.

To lay a solid foundation for data-driven approaches, I contributed in building large-scale knowledge-base of 2D images (ImageNet) and 3D shapes (ShapeNet), where rich semantical, visual, geometrical, and physical properties are stored.

Towards the goal, I also believe that it is essential to bridge two fields --- computer vision and computer graphics, where the former focuses on visual data analysis and the latter on geometrical and physical data analysis. I develop tools to link 2D and 3D data based upon geometry processing and machine learning techniques, especially deep learning.

Research Overview

Computer Vision and Computer Graphics
  • Joint Analysis of 2D Images and 3D Shapes
  • Crowd-sourcing for Large-scale Dataset Construction
  • Scene Understanding
Statistics and Optimization
  • Large-scale Optimization
  • Large-scale Graph Analysis
  • Multivariate Density Estimation

Publications

Computer Vision and Computer Graphics

Volumetric and Multi-View CNNs for Object Classification on 3D Data
Charles Qi*, Hao Su*, Matthias Niessner, Angela Dai, Mengyuan Yan, Leonidas Guibas
CVPR 2016 (spotlight oral)
ShapeNet: An Information-Rich 3D Model Repository
Angel X. Chang, Thomas Funkhouser, Leonidas Guibas, Pat Hanrahan, Qixing Huang, Zimo Li, Silvio Savarese, Manolis Savva*, Shuran Song, Hao Su*, Jianxiong Xiao, Li Yi, and Fisher Yu
Corresponding author, student lead
3D-Assisted Image Feature Synthesis for Novel Views of an Object
Hao Su*, Fan Wang*, Li Yi, Leonidas Guibas
ICCV 2015 (oral, acceptance rate: 2%)
Render for CNN: Viewpoint Estimation in Images Using CNNs Trained with Rendered 3D Model Views
Hao Su*, Charles Qi*, Yangyan Li, Leonidas Guibas
ICCV 2015 (oral, acceptance rate: 2%)
Joint Embeddings of Shapes and Images via CNN Image Purification
Hao Su*, Yangyan Li*, Charles Qi, Noa Fish, Daniel Cohen-Or, Leonidas Guibas
Transaction of Graphics (SIGGRAPH Asia 2015)
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky*, Jia Deng*, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, Li Fei-Fei
IJCV 2015
Estimating Image Depth using Shape Collections
Hao Su, Qixing Huang, Niloy Mitra, Yangyan Li, Leonidas Guibas
Transaction of Graphics (SIGGRAPH 2014)
Fine-Grained Semi-Supervised Labeling of Large Shape Collections
Qixing Huang, Hao Su, Leonidas Guibas
Transaction of Graphics (SIGGRAPH Asia 2013)
Multi-level structured image coding on high-dimensional image representation
Li-Jia Li*, Jun Zhu*, Hao Su, Eric.P. Xing, Li Fei-Fei
ACCV 2013
Crowd-sourcing Annotations for Visual Object Detection
Hao Su, Jia Deng, Li Fei-Fei
AAAI 2012 Human Computation Workshop
Object Bank: A High-Level Image Representation for Scene Classification & Semantic Feature Sparsification
Hao Su*, Li-Jia Li*, Eric.P. Xing, Li Fei-Fei
NIPS 2010 (top 10 most cited paper in NIPS since 2010)
Learning a dense multi-view representation for detection, viewpoint classification and synthesis of object categories
Hao Su*, Min Sun*, Li Fei-Fei and Silvio Savarese
ICCV 2009 (oral, acceptance rate: 4%)
A Multi-View Probabilistic Model for 3D Object Classes
Hao Su*, Min Sun*, Li Fei-Fei and Silvio Savarese
CVPR 2009
Construction and Analysis of a Large Scale Image Ontology
Jia Deng, Hao Su, Minh Do, Kai Li, Li Fei-Fei
VSS 2009

Statistics and Optimization

Density Estimation via Discrepancy
Kun Yang, Hao Su, Wing Wong
arXiv:1509.06831, 2015
co-BPM: a Bayesian Model for Estimating Divergence and Distance of Distributions
Kun Yang, Hao Su, Wing Wong
arXiv:1410.0726, 2014
Reverse Top-k Search using Random Walk with Restart
Adams Wei Yu, Nikos Mamoulis, Hao Su
VLDB 2014
Efficient Euclidean Projections onto the Intersection of Norm Balls
Hao Su*, Adams W. Yu*, Li Fei-Fei
ICML 2012

Misc

Pathlet Learning for Compressing and Planning Trajectories
Chen Chen, Hao Su, Qixing Huang, Lin Zhang, Leonidas Guibas
SIGSPATIAL 2013