I accomplished my Master's degree in Data Engineering and Signal Processing at Tampere University of Technology with
Prof. Joni Kämäräinen
and Prof. Ke Chen in 2017.
Prior to my doctoral study, I was a computer vision algorithm engineer working in Misshfresh Limited, Shenzhen, China.
We present an efficient symmetry-agnostic and correspondence-free framework, referred to as SC6D, for 6D object pose estimation
from a single monocular RGB image. SC6D requires neither the 3D CAD model of the object nor any prior knowledge of the symmetries.
We propose a universal object 6D pose estimation model, called OVE6D, purely trained on synthetic 3D objects from ShapeNet
and generalizing remarkably well to unseen objects without needing any parameter optimization.
We propose a novel resolution-aware deep model which combines convolutional image super-resolution and
convolutional fine-grained classification into a single model in an end-to-end manner.