Real-world single image super-resolution: A brief review
Single image super-resolution (SISR), which aims to reconstruct a high-resolution (HR)
image from a low-resolution (LR) observation, has been an active research topic in the area …
image from a low-resolution (LR) observation, has been an active research topic in the area …
Deep raw image super-resolution. a NTIRE 2024 challenge survey
This paper reviews the NTIRE 2024 RAW Image Super-Resolution Challenge highlighting
the proposed solutions and results. New methods for RAW Super-Resolution could be …
the proposed solutions and results. New methods for RAW Super-Resolution could be …
V?: Guided Visual Search as a Core Mechanism in Multimodal LLMs
When we look around and perform complex tasks how we see and selectively process what
we see is crucial. However the lack of this visual search mechanism in current multimodal …
we see is crucial. However the lack of this visual search mechanism in current multimodal …
Deep learning for image super-resolution: A survey
Image Super-Resolution (SR) is an important class of image processing techniqueso
enhance the resolution of images and videos in computer vision. Recent years have …
enhance the resolution of images and videos in computer vision. Recent years have …
Real-world super-resolution via kernel estimation and noise injection
Recent state-of-the-art super-resolution methods have achieved impressive performance on
ideal datasets regardless of blur and noise. However, these methods always fail in real …
ideal datasets regardless of blur and noise. However, these methods always fail in real …
Toward real-world single image super-resolution: A new benchmark and a new model
Most of the existing learning-based single image super-resolution (SISR) methods are
trained and evaluated on simulated datasets, where the low-resolution (LR) images are …
trained and evaluated on simulated datasets, where the low-resolution (LR) images are …
Component divide-and-conquer for real-world image super-resolution
In this paper, we present a large-scale Diverse Real-world image Super-Resolution dataset,
ie, DRealSR, as well as a divide-and-conquer Super-Resolution (SR) network, exploring the …
ie, DRealSR, as well as a divide-and-conquer Super-Resolution (SR) network, exploring the …
Depth pro: Sharp monocular metric depth in less than a second
A Bochkovskii, A Delaunoy, H Germain… - arxiv preprint arxiv …, 2024 - arxiv.org
We present a foundation model for zero-shot metric monocular depth estimation. Our model,
Depth Pro, synthesizes high-resolution depth maps with unparalleled sharpness and high …
Depth Pro, synthesizes high-resolution depth maps with unparalleled sharpness and high …
Deep burst super-resolution
While single-image super-resolution (SISR) has attracted substantial interest in recent years,
the proposed approaches are limited to learning image priors in order to add high frequency …
the proposed approaches are limited to learning image priors in order to add high frequency …
A text attention network for spatial deformation robust scene text image super-resolution
Scene text image super-resolution aims to increase the resolution and readability of the text
in low-resolution images. Though significant improvement has been achieved by deep …
in low-resolution images. Though significant improvement has been achieved by deep …