Kookmin University team develops technology to optimize 3D object detection models for self-driving
A Kookmin University research team has developed SharedKD, a technology that efficiently compresses 3D object detection models for autonomous driving, in collaboration with Hyundai Motor. The university said Tuesday that the findings were presented at the 2026 Design Automation Conference, a prestigious international conference in the field of design automation, held in Long Beach, California,…
A research team from Kookmin University, led by Professor Kim Jang-ho, has developed SharedKD, a technology designed to optimize 3D object detection models for autonomous driving. This collaboration with Hyundai Motor was recently presented at the prestigious 2026 Design Automation Conference, held in Long Beach, California, from July 26-29.
The SharedKD technology stands apart from conventional knowledge distillation methods, which typically utilize separate teacher and student models. In contrast, SharedKD employs the entire network of a single 3D object detection model as the teacher model and generates a subnetwork through pruning as the student model.
During the training process, SharedKD dynamically selects important structures based on gradients, allowing for efficient compression of 3D object detection models. This innovative approach was developed by Professor Kim Jang-ho and two master's students, Cho Hyun-joon and An Sang-ho, from the Graduate School of AI and SW.
Written by urgent.news from The Korea Times's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
