Hitchhiker's guide to super-resolution: Introduction and recent advances
With the advent of Deep Learning (DL), Super-Resolution (SR) has also become a thriving
research area. However, despite promising results, the field still faces challenges that …
research area. However, despite promising results, the field still faces challenges that …
Ultra-high-definition low-light image enhancement: A benchmark and transformer-based method
As the quality of optical sensors improves, there is a need for processing large-scale
images. In particular, the ability of devices to capture ultra-high definition (UHD) images and …
images. In particular, the ability of devices to capture ultra-high definition (UHD) images and …
Towards real-time 4k image super-resolution
Over the past few years, high-definition videos and images in 720p (HD), 1080p (FHD), and
4K (UHD) resolution have become standard. While higher resolutions offer improved visual …
4K (UHD) resolution have become standard. While higher resolutions offer improved visual …
Efficient deep models for real-time 4k image super-resolution. NTIRE 2023 benchmark and report
This paper introduces a novel benchmark for efficient upscaling as part of the NTIRE 2023
Real-Time Image Super-Resolution (RTSR) Challenge, which aimed to upscale images …
Real-Time Image Super-Resolution (RTSR) Challenge, which aimed to upscale images …
Deep neural network for blind visual quality assessment of 4K content
The 4K content can deliver a more immersive visual experience to consumers due to the
huge improvement in spatial resolution. However, the high spatial resolution brings a great …
huge improvement in spatial resolution. However, the high spatial resolution brings a great …
Beyond monocular deraining: Parallel stereo deraining network via semantic prior
Rain is a common natural phenomenon. Taking images in the rain however often results in
degraded quality of images, thus compromises the performance of many computer vision …
degraded quality of images, thus compromises the performance of many computer vision …
Honeycomb: Secure and Efficient {GPU} Executions via Static Validation
Graphics Processing Units (GPUs) unlock emerging use cases like large language models
and autonomous driving. They process a large amount of sensitive data, where security is of …
and autonomous driving. They process a large amount of sensitive data, where security is of …
Blind face restoration: Benchmark datasets and a baseline model
Abstract Blind Face Restoration (BFR) aims to generate high-quality face images from low-
quality inputs. However, existing BFR methods often use private datasets for training and …
quality inputs. However, existing BFR methods often use private datasets for training and …
Comparing the robustness of modern no-reference image-and video-quality metrics to adversarial attacks
A Antsiferova, K Abud, A Gushchin… - Proceedings of the …, 2024 - ojs.aaai.org
Nowadays neural-network-based image-and video-quality metrics show better performance
compared to traditional methods. However, they also became more vulnerable to …
compared to traditional methods. However, they also became more vulnerable to …
Uhd-iqa benchmark database: Pushing the boundaries of blind photo quality assessment
We introduce a novel Image Quality Assessment (IQA) dataset comprising 6073 UHD-1 (4K)
images, annotated at a fixed width of 3840 pixels. Contrary to existing No-Reference (NR) …
images, annotated at a fixed width of 3840 pixels. Contrary to existing No-Reference (NR) …