Title of the paper: SoftGroup for 3D Instance Segmentation on Point Clouds
Conference: The IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR) 2022
Date & Location: June 21, 2022 (Tue) / New Orleans, Louisiana, USA
[(from the left) Professor Chang D. Yoo, Vu Van Thang (Ph.D candidate), Kookhoi Kim (Master’s candidate)]
3D datasets are being utilized in various fields recently such as autonomous driving, robotics, and AR. 3D point clouds are data comprised of sets of 3D points and this study developed SoftGroup, a precision object segmentation technology based on 3D point cloud. SoftGroup allows each point to be associated with multiple classes to mitigate problems stemming from semantic prediction errors and surpasses prior state-of-the-art methods by more than 8% in terms of performance. Allowing for 3D instance segmentation of point clouds that contain more precise information of 3D space compared to traditional photographs, SoftGroup shows high potential for utilization in fields that leverage 3D point clouds.
