Search Results for author: Youngjung Kim

Found 7 papers, 1 papers with code

GuideFormer: Transformers for Image Guided Depth Completion

no code implementations CVPR 2022 Kyeongha Rho, Jinsung Ha, Youngjung Kim

Depth completion has been widely studied to predict a dense depth image from its sparse measurement and a single color image.

Depth Completion

DIML/CVL RGB-D Dataset: 2M RGB-D Images of Natural Indoor and Outdoor Scenes

no code implementations22 Oct 2021 Jaehoon Cho, Dongbo Min, Youngjung Kim, Kwanghoon Sohn

This manual is intended to provide a detailed description of the DIML/CVL RGB-D dataset.

A Large RGB-D Dataset for Semi-supervised Monocular Depth Estimation

no code implementations23 Apr 2019 Jaehoon Cho, Dongbo Min, Youngjung Kim, Kwanghoon Sohn

In this paper, we present a simple yet effective approach for monocular depth estimation using stereo image pairs.

Monocular Depth Estimation Semantic Segmentation

Deeply Aggregated Alternating Minimization for Image Restoration

no code implementations CVPR 2017 Youngjung Kim, Hyungjoo Jung, Dongbo Min, Kwanghoon Sohn

The proposed framework enables the convolutional neural networks (CNNs) to operate as a prior or regularizer in the AM algorithm.

Image Denoising Image Restoration +1

Efficient Splitting-based Method for Global Image Smoothing

no code implementations26 Apr 2016 Youngjung Kim, Dongbo Min, Bumsub Ham, Kwanghoon Sohn

In this paper, we introduce a highly efficient splitting-based method for global EPS that minimizes the objective function of ${l_2}$ data and prior terms (possibly non-smooth and non-convex) in linear time.

image smoothing

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