Kookmin University team develops technology to optimize 3D object detection models for self-driving

Kookmin University researchers, led by professor Kim Jang-ho, developed SharedKD, a technology that compresses 3D object detection models for autonomous driving, in collaboration with Hyundai Motor. The findings were presented at the 2026 Design Automation Conference in Long Beach, California, from July 26-29. SharedKD uses a single model's entire network as the teacher and a pruned subnetwork as the student, dynamically selecting important structures based on gradients.

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, from July 26-29. Kim Jang-ho, a professor at the university’s College of Computer Science, led the research team. Two master’s students at the Graduate School of AI and SW, Cho Hyun-joon and An Sang-ho, also participated in the study and contributed to the development of the technology. The university noted that the SharedKD technology differs from conventional knowledge distillation methods that use separate teacher and student models. Instead, SharedKD uses the entire network of a single 3D object detection model as the teacher model and a subnetwork generated through pruning as the student model. During training, SharedKD dynamically selects important structures based on gradients, enabling i