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20182022
most citedForget About the LiDAR: Self-Supervised Depth Estimators with MED Probability Volumes

40 citations · 96 across the 13 of their papers we have counts for

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Showing eess.IVShow all

8 papers · 1 filter

eess.IV20229 cited

Selective compression learning of latent representations for variable-rate image compression

Jooyoung Lee, Seyoon Jeong, Munchurl Kim

Recently, many neural network-based image compression methods have shown promising results superior to the existing tool-based conventional codecs. However, most of them are often…

eess.IV2022

Realistic Bokeh Effect Rendering on Mobile GPUs, Mobile AI & AIM 2022 challenge: Report

Andrey Ignatov, Radu Timofte, Jin Zhang +21

As mobile cameras with compact optics are unable to produce a strong bokeh effect, lots of interest is now devoted to deep learning-based solutions for this task. In this Mobile AI…

eess.IV2020

Pan-Sharpening with Color-Aware Perceptual Loss and Guided Re-Colorization

Juan Luis Gonzalez Bello, Soomin Seo, Munchurl Kim

We present a novel color-aware perceptual (CAP) loss for learning the task of pan-sharpening. Our CAP loss is designed to focus on the deep features of a pre-trained VGG network th…

eess.IV2019

An End-to-End Joint Learning Scheme of Image Compression and Quality Enhancement with Improved Entropy Minimization

Jooyoung Lee, Seunghyun Cho, Munchurl Kim

Recently, learned image compression methods have been actively studied. Among them, entropy-minimization based approaches have achieved superior results compared to conventional im…

eess.IV20194 cited

Deep 3D-Zoom Net: Unsupervised Learning of Photo-Realistic 3D-Zoom

Juan Luis Gonzalez Bello, Munchurl Kim

The 3D-zoom operation is the positive translation of the camera in the Z-axis, perpendicular to the image plane. In contrast, the optical zoom changes the focal length and the digi…

eess.IV2019

JSI-GAN: GAN-Based Joint Super-Resolution and Inverse Tone-Mapping with Pixel-Wise Task-Specific Filters for UHD HDR Video

Soo Ye Kim, Jihyong Oh, Munchurl Kim

Joint learning of super-resolution (SR) and inverse tone-mapping (ITM) has been explored recently, to convert legacy low resolution (LR) standard dynamic range (SDR) videos to high…