Sparse-view Pose Estimation and Reconstruction via Analysis by Generative Synthesis - Robotics Institute Carnegie Mellon University

VASC Seminar

October

28
Mon
Qitao Zhao Master's Student Computer Vision, Carnegie Mellon University
Monday, October 28
3:30 pm to 4:30 pm
3305 Newell-Simon Hall
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Sparse-view Pose Estimation and Reconstruction via Analysis by Generative Synthesis
Abstract:  This talk will present our approach for reconstructing objects from sparse-view images captured in unconstrained environments. In the absence of ground-truth camera poses, we will demonstrate how to utilize estimates from off-the-shelf systems and address two key challenges: refining noisy camera poses in sparse views and effectively handling outlier poses.
 
Bio:  Qitao is a second-year Master’s student in Computer Vision at CMU, RI, advised by Prof. Shubham Tulsiani. His research focuses on camera pose estimation and 3D reconstruction in the wild. He holds a Bachelor’s degree from Shandong University in China and was a visiting student at the University of Central Florida, where he worked with Prof. Chen Chen.
 
Homepage:  https://qitaozhao.github.io/
Sponsored in part by:   Meta Reality Labs Pittsburgh