Deep learning in pore scale imaging and modeling
Pore-scale imaging and modeling has advanced greatly through the integration of Deep
Learning into the workflow, from image processing to simulating physical processes. In …
Learning into the workflow, from image processing to simulating physical processes. In …
Ntire 2020 challenge on real-world image super-resolution: Methods and results
A Lugmayr, M Danelljan… - Proceedings of the IEEE …, 2020 - openaccess.thecvf.com
This paper reviews the NTIRE 2020 challenge on real world super-resolution. It focuses on
the participating methods and final results. The challenge addresses the real world setting …
the participating methods and final results. The challenge addresses the real world setting …
Fine perceptive gans for brain mr image super-resolution in wavelet domain
Magnetic resonance (MR) imaging plays an important role in clinical and brain exploration.
However, limited by factors such as imaging hardware, scanning time, and cost, it is …
However, limited by factors such as imaging hardware, scanning time, and cost, it is …
Fourier space losses for efficient perceptual image super-resolution
Many super-resolution (SR) models are optimized for high performance only and therefore
lack efficiency due to large model complexity. As large models are often not practical in real …
lack efficiency due to large model complexity. As large models are often not practical in real …
Ntire 2020 challenge on spectral reconstruction from an rgb image
This paper reviews the second challenge on spectral reconstruction from RGB images, ie,
the recovery of whole-scene hyperspectral (HS) information from a 3-channel RGB image …
the recovery of whole-scene hyperspectral (HS) information from a 3-channel RGB image …
Aim 2020 challenge on efficient super-resolution: Methods and results
This paper reviews the AIM 2020 challenge on efficient single image super-resolution with
focus on the proposed solutions and results. The challenge task was to super-resolve an …
focus on the proposed solutions and results. The challenge task was to super-resolve an …
Efficient and accurate quantized image super-resolution on mobile NPUs, mobile AI & AIM 2022 challenge: report
Image super-resolution is a common task on mobile and IoT devices, where one often needs
to upscale and enhance low-resolution images and video frames. While numerous solutions …
to upscale and enhance low-resolution images and video frames. While numerous solutions …
Ntire 2020 challenge on nonhomogeneous dehazing
This paper reviews the NTIRE 2020 Challenge on NonHomogeneous Dehazing of images
(restoration of rich details in hazy image). We focus on the proposed solutions and their …
(restoration of rich details in hazy image). We focus on the proposed solutions and their …
Real-time quantized image super-resolution on mobile npus, mobile ai 2021 challenge: Report
Image super-resolution is one of the most popular computer vision problems with many
important applications to mobile devices. While many solutions have been proposed for this …
important applications to mobile devices. While many solutions have been proposed for this …
Perceptual extreme super-resolution network with receptive field block
T Shang, Q Dai, S Zhu, T Yang… - Proceedings of the IEEE …, 2020 - openaccess.thecvf.com
Abstract Perceptual Extreme Super-Resolution for single image is extremely difficult,
because the texture details of different images vary greatly. To tackle this difficulty, we …
because the texture details of different images vary greatly. To tackle this difficulty, we …