Songfang Han

Ph.D.

EMAIL

hansongfang
[at]gmail[dot]com

News

  • July, 2021 - Two paper get accepted to ICCV2021.
  • Apr, 2021 - Our ICCV2021 Workshop Call-for-paper: StruCo3D2021: Structural and Compositional Learning on 3D Data.
  • Feb, 2021 - One paper gets accepted to TVCG.
  • Apr, 2020 - One paper gets accepted to TPAMI.
  • July, 2019 - One paper gets accepted to ICCV2019 (oral).
  • Jun, 2019 - Has successfully defended my Ph.D. thesis!

Intro

I have obtained my Ph.D. degree at HKUST, advised by Prof. Pedro Sander. During the Spring 2019, I was a visiting student to the University of California, San Diego, supervised by Prof. Hao Su. For the autumn 2017, I was a research intern at SenseTime, supervised by Dr. Qiong Yan. Before that, I received my B.S. degree in EE department from Tongji University in 2013.

Since April 2020, I have started at SULab as a postdoctoral researcher, working with Prof. Hao Su.

My research interest includes computer graphics and computer vision, especially in 3D geometry processing, 3D reconstruction. My work covers efficient rendering, multi-view reconstruction, portrait relighting and virtual reality.

[CV].

Research

2021

Learning with Noisy Labels for Robust Point Cloud Segmentation
Shuquan Ye, Dongdong Chen, Songfang Han, Jing Liao.
International Conference on Computer Vision (ICCV Oral), 2021
[project (code)] [paper] [code]

M3D-VTON: A Monocular-to-3D Virtual Try-On Network
Fuwei Zhao, Zhenyu Xie, Michael Kampffmeyer, Haoye Dong, Songfang Han, Tianxiang Zheng, Tao Zhang, Xiaodan Liang.
International Conference on Computer Vision (ICCV), 2021.
[paper] [code]

Compositionally Generalizable 3D Structure Prediction
Songfang Han, Jiayuan Gu, Kaichun Mo, Li Yi, Siyu Hu, Xuejin Chen, Hao Su.
arXiv, 2021.
[paper] [code] [video]

Arbitrary-Scale Upsampling Network for Point Cloud
Shuquan Ye, Dongdong Chen, Songfang Han, Ziyu Wan, Jing Liao.
Visualization and Computer Graphics (TVCG), 2021.
[project (code)] [paper]

2020

Visibility-Aware Point-Based Multi-View Stereo Network
Rui Chen, Songfang Han, Jing Xu.
TPAMI 2020 Apr 22. doi: 10.1109/TPAMI.2020.2988729.
[project (code)] [paper]
This is an extension of our ICCV work (Point-based Multi-view Stereo Network). In this paper, we introduce visibility-aware multi-view feature aggregation modules to gather information from visible views only for better depth prediction accuracy.

2019

Point-Based Multi-View Network
Songfang Han*, Rui Chen*, Jing Xu, Hao Su.
ICCV 2019 (oral).
[project (code)] [paper] [video]
An iterative framework to predict the depth of a scene using point cloud representation from multiple views. Use deep learning over the kNN graph to predict the residual for geometry estimation refinement.

2018

In-Depth Buffers
Songfang Han, Ge Chen, Diego Nehab, Pedro Sander.
Proceedings of the ACM on Computer Graphics and Interactive Techniques (PACM) 2018.
[paper] [code] [video]

2017

Triangle Reordering for Efficient Rendering in Complex Scenes
Songfang Han, Pedro Sander.
The Journal of Computer Graphics Techniques (JCGT) 2017.
[paper] [code] [video]

2016

Triangle Reordering for Reduced Overdraw in Animated Scenes
Songfang Han, Pedro Sander.
Proceedings of the 20th ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games (I3D) 2016.
[paper]