Our paper, titled “Real-Time Joint Semantic Segmentation and Depth Estimation Using Asymmetric Annotations” has recently been accepted at International Conference on Robotics and Automation (ICRA 2019), which will take place in Montreal, Canada in May. This was a joint work between the University of Adelaide and Monash University, and it was a great experience for me learning from my collaborators about two dense per-pixel tasks that I had only been vaguely familiar with before: depth estimation – i.e., predicting how far each pixel is from the observer, and surface normals estimation – i.e., predicting a perpendicular vector (normal vector) to each pixel’s surface. Both tasks are extremely valuable in the robotic community, and hence we were motivated to explore the limits of performing three tasks (2 above + semantic segmentation) in real-time using a single network.
|Segmenting a turtle - one of the slowest animals on Earth: left - original photo, right - segmentation result (highlighted in different colour)|
After nearly two years from my first publication (at the same venue as now), which included a year of academic break, I have finally submitted my first paper in my new PhD journey to the BMVC conference, which will take place from Sep, 3 to Sep, 6 in Newcastle-upon-Tyne. This time it took me a month more for the submission, although all the main results were in place already in March.