Search Results for author: Eojindl Yi

Found 5 papers, 2 papers with code

PBP-Net: Point Projection and Back-Projection Network for 3D Point Cloud Segmentation

no code implementations2 Nov 2020 JuYoung Yang, Chanho Lee, Pyunghwan Ahn, Haeil Lee, Eojindl Yi, Junmo Kim

In this paper, we propose a simple and efficient architecture named point projection and back-projection network (PBP-Net), which leverages 2D CNNs for the 3D point cloud segmentation.

Point Cloud Segmentation Segmentation +1

An empirical study of a pruning mechanism

1 code implementation1 Jan 2021 Minju Jung, Hyounguk Shon, Eojindl Yi, SungHyun Baek, Junmo Kim

For the pruning and retraining phase, whether the pruned-and-retrained network benefits from the pretrained network indded is examined.

Network Pruning

Projection-based Point Convolution for Efficient Point Cloud Segmentation

1 code implementation4 Feb 2022 Pyunghwan Ahn, JuYoung Yang, Eojindl Yi, Chanho Lee, Junmo Kim

Point branch consists of MLPs, while projection branch transforms point features into a 2D feature map and then apply 2D convolutions.

Point Cloud Segmentation

Lightweight Monocular Depth Estimation via Token-Sharing Transformer

no code implementations9 Jun 2023 Dong-Jae Lee, Jae Young Lee, Hyounguk Shon, Eojindl Yi, Yeong-Hun Park, Sung-Sik Cho, Junmo Kim

While most lightweight monocular depth estimation methods have been developed using convolution neural networks, the Transformer has been gradually utilized in monocular depth estimation recently.

Depth Prediction Monocular Depth Estimation

Cannot find the paper you are looking for? You can Submit a new open access paper.