3 citations · 6 across the 5 of their papers we have counts for
4 papers · 1 filter
FS-NCSR: Increasing Diversity of the Super-Resolution Space via Frequency Separation and Noise-Conditioned Normalizing Flow
Ki-Ung Song, Dongseok Shim, Kang-wook Kim +2
Super-resolution suffers from an innate ill-posed problem that a single low-resolution (LR) image can be from multiple high-resolution (HR) images. Recent studies on the flow-based…
Learning a Domain-Agnostic Visual Representation for Autonomous Driving via Contrastive Loss
Dongseok Shim, H. Jin Kim
Deep neural networks have been widely studied in autonomous driving applications such as semantic segmentation or depth estimation. However, training a neural network in a supervis…
Gaussian RAM: Lightweight Image Classification via Stochastic Retina-Inspired Glimpse and Reinforcement Learning
Dongseok Shim, H. Jin Kim
Previous studies on image classification have mainly focused on the performance of the networks, not on real-time operation or model compression. We propose a Gaussian Deep Recurre…
Learning a Geometric Representation for Data-Efficient Depth Estimation via Gradient Field and Contrastive Loss
Dongseok Shim, H. Jin Kim
Estimating a depth map from a single RGB image has been investigated widely for localization, mapping, and 3-dimensional object detection. Recent studies on a single-view depth est…