Welcome to Hao Su's homepage (original) (raw)

Publications

Computer Vision and Computer Graphics

Cross-modal Attribute Transfer for Rescaling 3D Models

3DV 2017

Transfer geometrical and physical attributes from product catelog to 3D models in ShapeNet.

PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

Charles R. Qi, Li Yi, Hao Su, Leonidas J. Guibas

NIPS 2017

Deep network architecture for processing point cloud of cluttered scenes that often have non-uniform sampling density. Build upon PointNet, our CVPR2017 paper.

ComplementMe: Weakly-Supervised Component Suggestions for 3D Modeling

Minhyuk Sung, Hao Su, Vladimir G. Kim, Siddhartha Chaudhuri, and Leonidas Guibas

SIGGRAPH Asia 2017

Deep learning based approach for part-based 3D model synthesis. Given a partial construction (e.g., a chair in design), this method proposes a new component (e.g., arm) that is compatible with existing shape in style.

Learning Hierarchical Shape Segmentation and Labeling from Online Repositories

Li Yi, Leonidas J. Guibas, Aaron Hertzmann, Vladimir G. Kim, Hao Su, Ersin Yumer

SIGGRAPH 2017

Learn a consistent part hierarchy from a large collection of 3D models with scene-graph structure.

A Point Set Generation Network for 3D Object Reconstruction from a Single Image

Hao Su*, Haoqiang Fan*, Leonidas Guibas

CVPR 2017 (oral)

Build a generative neural network to directly output a set of unordered points. As applications, it can be used for single-image based 3D reconstruction and shape completion.

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

Hao Su*, Charles Qi*, Kaichun Mo, Leonidas Guibas

CVPR 2017 (oral)

Build a neural network to directly consume an unordered point cloud as input, without converting to other 3D representations such as voxel grids first. Rich theoretical and empirical analyses are provided.

SyncSpecCNN: Synchronized Spectral CNN for 3D Shape Segmentation

Li Yi, Hao Su, Xingwen Guo, Leonidas Guibas

CVPR 2017 (spotlight)

A convolutional neural network on generic graphs of non-isometric structures. Spectral analysis (spectral domain synchronization) is conducted to enable effective kernel weight sharing. Part segmentation as an application.

Learning Shape Abstractions by Assembling Volumetric Primitives

Shubham Tulsiani, Hao Su, Leonidas Guibas, Alexei A. Efros, Jitendra Malik

CVPR 2017

Learn to abstract polygonal meshes by a flexible number of simple primitives such as cuboids. The abstraction is category consistent.

Learning Non-Lambertian Object Intrinsics across ShapeNet Categories

Jian Shi, Yue Dong, Hao Su, Stella X. Yu

CVPR 2017

Show that the material attributes of ShapeNet models can be useful to train algorithms for understanding the material and optical properties in Internet photos.

Beyond Holistic Object Recognition: Enriching Image Understanding with Part States

Cewu Lu, Hao Su, Yongyi Lu, Li Yi, Chikeung Tang, Leonidas Guibas

arxiv, 2016

Introduce the concept and computational model of "part state", an intermediate representation for object interaction modeling and image captioning. A dataset is provided, as well.

Volumetric and Multi-View CNNs for Object Classification on 3D Data

Hao Su*, Charles Qi*, Matthias Niessner, Angela Dai, Mengyuan Yan, Leonidas Guibas

CVPR 2016 (spotlight oral)

Novel architectures for 3DCNNs that take volumetric or multi-view representations as input.

Multilinear Hyperplane Hashing

Xianglong Liu, Xinjie Fan, Cheng Deng, Hao Su, Dacheng Tao

CVPR 2016

Efficient approximate point-to-plane search.

Synthesizing Training Images for Boosting Human 3D Pose Estimation

Wenzheng Chen, Huan Wang, Yangyan Li, Hao Su, Zhenhua Wang, Chenghe Tu, Dani Lischinski, Daniel Cohen-Or, Baoquan Chen

3DV 2016 (oral)

Extend RenderForCNN (my ICCV'15 paper) for 3D human pose estimation focusing on domain adaptation and data augmentation by automatic texture transfer.

ObjectNet3D: A Large Scale Database for 3D Object Recognition

Yu Xiang, Wonhui Kim, Wei Chen, Jingwei Ji, Christopher Choy, Hao Su, Roozbeh Mottaghi, Leonidas Guibas, Silvio Savarese

ECCV 2016 (spotlight oral)

A large-scale image-shape database by linking ImageNet and ShapeNet at instance level.

3D Attention-Driven Depth Acquisition for Object Identification

Kai Xu, Yifei Shi, Lintao Zheng, Junyu Zhang, Min Liu, Hui Huang, Hao Su, Daniel Cohen-Or, Baoquan Chen

Transactions on Graphics (SIGGRAPH ASIA 2016)

Teach robots to identify objects with fewest movements and scans. We trained a 3D attention model by reinforcement learning.

Unsupervised Texture Transfer from Images to Model Collections

Tuanfeng Y. Wang, Hao Su, Qixing Huang, Jingwei Huang, Leonidas J. Guibas, Niloy J. Mitra

Transactions on Graphics (SIGGRAPH ASIA 2016)

Transfer textures from product images to 3D shapes. The increased texture variation in ShapeNet is validated to be effective for RenderForCNN (my ICCV'15 paper).

A Scalable Active Framework for Region Annotation in 3D Shape Collections

Li Yi, Vladimir G. Kim, Duygu Ceylan, I-Chao Shen, Mengyuan Yan, Hao Su, Cewu Lu, Qixing Huang, Alla Sheffer, Leonidas Guibas

Transactions on Graphics (SIGGRAPH ASIA 2016)

Annotate the parts for ShapeNet by crowd-sourcing and label propagation with high efficiency and accuracy.

SHREC’16 Track: Large-Scale 3D Shape Retrieval from ShapeNet Core55

M. Savva, F. Yu, Hao Su, M. Aono, B. Chen, D. Cohen-Or, W. Deng, H. Su, S. Bai, X. Bai, N. Fish, J. Han, E. Kalogerakis, E. G. Learned-Miller, Y. Li, M. Liao, S. Maji, A. Tatsuma, Y. Wang, N. Zhang, Z. Zhou

EuroGraphics SHREC2016 Workshop Report

Technical report for SHREC'16, the most renowned challenge for 3D shape retrieval.

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, Fisher Yu

Corresponding author, student co-lead, arxiv, 2016

The official report of ShapeNet, an object-centric database of semantics, geometry and physics.

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%)

Synthesize features at novel views of a 3D object from the observed viewpoint, leveraging on the geometric priors from ShapeNet.

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%)

Show that large-scale synthetic data rendered from virtual world may greatly benefit deep learning to work in real world. Deliver a state-of-the-art viewpoint estimator.

Joint Embeddings of Shapes and Images via CNN Image Purification

Hao Su*, Yangyan Li*, Charles Qi, Noa Fish, Daniel Cohen-Or, Leonidas Guibas

Transactions on Graphics (SIGGRAPH Asia 2015)

Cross-modality learning of 3D shapes and 2D images by neural networks. A joint embedding space that is sensitive to 3D geometry difference but agnostic to other nuisances is constructed.

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

The technical report for ImageNet Challenge.

Estimating Image Depth using Shape Collections

Hao Su, Qixing Huang, Niloy Mitra, Yangyan Li, Leonidas Guibas

Transactions on Graphics (SIGGRAPH 2014)

Learn to estimate the depth from a single input image assisted by geometric priors from a 3D shape collection (later merged to ShapeNet).

Fine-Grained Semi-Supervised Labeling of Large Shape Collections

Qixing Huang, Hao Su, Leonidas Guibas

Transactions on Graphics (SIGGRAPH Asia 2013)

Fine-grained 3D shape classification.

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

Multi-layer sparse coding for compressing ObjectBank representation.

Crowd-sourcing Annotations for Visual Object Detection

Hao Su, Jia Deng, Li Fei-Fei

AAAI 2012 Human Computation Workshop

A system to annotate object bounding boxes for ImageNet by crowd-sourcing. This system is used to collect bounding boxes for ImageNet Large Scale Visual Recognition Challenges.

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)

Learn to describe scenes by responses from object detectors. Can be viewed as a layer-wise trained CNN (Gradient-HoG-Part-Object-Scene hierarchy).

Learning a dense multi-view representation for detection, viewpoint classification and synthesis of object categories

Hao Su*, Min Sun*, Li Fei-Fei, Silvio Savarese

ICCV 2009 (oral, acceptance rate: 4%)

Continuous viewpoint estimation by a graphical model.

A Multi-View Probabilistic Model for 3D Object Classes

Hao Su*, Min Sun*, Li Fei-Fei, Silvio Savarese

CVPR 2009

Discrete viewpoint estimation by a graphical model.

Construction and Analysis of a Large Scale Image Ontology

Jia Deng, Hao Su, Minh Do, Kai Li, Li Fei-Fei

VSS 2009

ImageNet analysis paper.

Statistics and Optimization

FPNN: Field Probing Neural Networks for 3D Data

Yangyan Li, Soeren Pirk, Hao Su, Charles R. Qi, Leonidas J. Guibas

NIPS 2016

A very efficient 3D deep learning method for volumetric data processing that takes advantage of data sparsity in 3D fields.

Density Estimation via Discrepancy

Kun Yang, Hao Su, Wing Wong

arXiv:1509.06831, 2015

Estimating the density of a population by adaptively partitioning the space according to discrepancy criteria.

co-BPM: a Bayesian Model for Estimating Divergence and Distance of Distributions

Kun Yang, Hao Su, Wing Wong

Journal of Computational and Graphical Statistics

Measuring discrepancy of two samples by a Bayesian approach.

Reverse Top-k Search using Random Walk with Restart

Adams Wei Yu, Nikos Mamoulis, Hao Su

VLDB 2014

Given a node in a large-scale transition graph, how to efficiently find those nodes that have this given node as a top k nearest neighbour (reverse top-k search problem). The inverse of PageRank problem.

Efficient Euclidean Projections onto the Intersection of Norm Balls

Hao Su*, Adams W. Yu*, Li Fei-Fei

ICML 2012

Sparse-group LASSO model is a linear regression model that encourages simultaneous element-wise sparsity and group-wise sparsity. This work studies the key component in optimizing such a model by projection-based algorithms.

Misc

Pathlet Learning for Compressing and Planning Trajectories

Chen Chen, Hao Su, Qixing Huang, Lin Zhang, Leonidas Guibas

SIGSPATIAL 2013

Discover common sub-structures from a large set of taxi trajectories. Formulated as a linear programming problem, in a spirit similar to probabilistic topic models (pLSA).