3 citations · 5 across the 5 of their papers we have counts for
5 papers
Masked Spatial Propagation Network for Sparsity-Adaptive Depth Refinement
Jinyoung Jun, Jae-Han Lee, Chang-Su Kim
The main function of depth completion is to compensate for an insufficient and unpredictable number of sparse depth measurements of hardware sensors. However, existing research on…
Versatile Depth Estimator Based on Common Relative Depth Estimation and Camera-Specific Relative-to-Metric Depth Conversion
Jinyoung Jun, Jae-Han Lee, Chang-Su Kim
A typical monocular depth estimator is trained for a single camera, so its performance drops severely on images taken with different cameras. To address this issue, we propose a ve…
Depth Map Decomposition for Monocular Depth Estimation
Jinyoung Jun, Jae-Han Lee, Chul Lee +1
We propose a novel algorithm for monocular depth estimation that decomposes a metric depth map into a normalized depth map and scale features. The proposed network is composed of a…
RD-Optimized Trit-Plane Coding of Deep Compressed Image Latent Tensors
Seungmin Jeon, Jae-Han Lee, Chang-Su Kim
DPICT is the first learning-based image codec supporting fine granular scalability. In this paper, we describe how to implement two key components of DPICT efficiently: trit-plane…
DPICT: Deep Progressive Image Compression Using Trit-Planes
Jae-Han Lee, Seungmin Jeon, Kwang Pyo Choi +2
We propose the deep progressive image compression using trit-planes (DPICT) algorithm, which is the first learning-based codec supporting fine granular scalability (FGS). First, we…