Guan Pang

Guan leads the Rosetta OCR project, working to understand text in images and videos at scale, to identify inappropriate or harmful content and keep the community safe. He has also worked on 3D object detection with the Terragraph project. Guan developed a semantic segmentation module in the Map With AI project for country-scale satellite imagery road mapping in OpenStreetMap, and he co-organized the DeepGlobe challenge at CVPR 2018. He holds a Ph.D. from the University of Southern California, and an M.S. and B.Eng from Tsinghua University.

Guan's Publications

April 07, 2020

RESEARCH

COMPUTER VISION

From Satellite Imagery to Disaster Insights

The use of satellite imagery has become increasingly popular for disaster monitoring and response. After a disaster, it is important to prioritize rescue operations, disaster response and coordinate relief efforts. These have to be carried out…

Jigar Doshi, Saikat Basu, Guan Pang,

April 07, 2020

April 07, 2020

RESEARCH

COMPUTER VISION

Self-Supervised Feature Learning for Semantic Segmentation of Overhead Imagery

Overhead imageries play a crucial role in many applications such as urban planning, crop yield forecasting, mapping, and policy making. Semantic segmentation could enable automatic, efficient, and large-scale understanding of overhead imageries…

Suriya Singh, Anil Batra, Guan Pang, Lorenzo Torresani, Saikat Basu, Manohar Paluri, C.V. Jawahar,

April 07, 2020

April 07, 2020

RESEARCH

COMPUTER VISION

DeepGlobe 2018: A Challenge to Parse the Earth through Satellite Images

We present the DeepGlobe 2018 Satellite Image Understanding Challenge, which includes three public competitions for segmentation, detection, and classification tasks on satellite images (Figure 1). Similar to other challenges in computer vision…

Ilke Demir, Krzysztof Koperski, David Lindenbaum, Guan Pang, Jing Huang, Saikat Basu, Forest Hughes, Devis Tuia, Ramesh Raskar,

April 07, 2020