5 citations · 10 across the 3 of their papers we have counts for
3 papers
cs.DC2025★ 5 cited
PointSplit: Towards On-device 3D Object Detection with Heterogeneous Low-power Accelerators
Keondo Park, You Rim Choi, Inhoe Lee +1
Running deep learning models on resource-constrained edge devices has drawn significant attention due to its fast response, privacy preservation, and robust operation regardless of…
cs.CV2022
UpCycling: Semi-supervised 3D Object Detection without Sharing Raw-level Unlabeled Scenes
Sunwook Hwang, Youngseok Kim, Seongwon Kim +2
Semi-supervised Learning (SSL) has received increasing attention in autonomous driving to reduce the enormous burden of 3D annotation. In this paper, we propose UpCycling, a novel…
cs.LG2022★ 5 cited
Federated Semi-Supervised Learning with Prototypical Networks
Woojung Kim, Keondo Park, Kihyuk Sohn +2
With the increasing computing power of edge devices, Federated Learning (FL) emerges to enable model training without privacy concerns. The majority of existing studies assume the…