NTIRE 2024 challenge on bracketing image restoration and enhancement: Datasets methods and results
Low-light photography presents significant challenges. Multi-image processing methods
have made numerous attempts to obtain high-quality photos yet remain unsatisfactory …
have made numerous attempts to obtain high-quality photos yet remain unsatisfactory …
Deep learning for hdr imaging: State-of-the-art and future trends
L Wang, KJ Yoon - IEEE transactions on pattern analysis and …, 2021 - ieeexplore.ieee.org
High dynamic range (HDR) imaging is a technique that allows an extensive dynamic range
of exposures, which is important in image processing, computer graphics, and computer …
of exposures, which is important in image processing, computer graphics, and computer …
Pseudoinverse-guided diffusion models for inverse problems
Diffusion models have become competitive candidates for solving various inverse problems.
Models trained for specific inverse problems work well but are limited to their particular use …
Models trained for specific inverse problems work well but are limited to their particular use …
Local color distributions prior for image enhancement
Existing image enhancement methods are typically designed to address either the over-or
under-exposure problem in the input image. When the illumination of the input image …
under-exposure problem in the input image. When the illumination of the input image …
Text2light: Zero-shot text-driven hdr panorama generation
High-quality HDRIs (High Dynamic Range Images), typically HDR panoramas, are one of
the most popular ways to create photorealistic lighting and 360-degree reflections of 3D …
the most popular ways to create photorealistic lighting and 360-degree reflections of 3D …
Hdr-gan: Hdr image reconstruction from multi-exposed ldr images with large motions
Y Niu, J Wu, W Liu, W Guo… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Synthesizing high dynamic range (HDR) images from multiple low-dynamic range (LDR)
exposures in dynamic scenes is challenging. There are two major problems caused by the …
exposures in dynamic scenes is challenging. There are two major problems caused by the …
ADNet: Attention-guided deformable convolutional network for high dynamic range imaging
In this paper, we present an attention-guided deformable convolutional network for hand-
held multi-frame high dynamic range (HDR) imaging, namely ADNet. This problem …
held multi-frame high dynamic range (HDR) imaging, namely ADNet. This problem …
Invertible image signal processing
Unprocessed RAW data is a highly valuable image format for image editing and computer
vision. However, since the file size of RAW data is huge, most users can only get access to …
vision. However, since the file size of RAW data is huge, most users can only get access to …
Hdrunet: Single image hdr reconstruction with denoising and dequantization
Most consumer-grade digital cameras can only capture a limited range of luminance in real-
world scenes due to sensor constraints. Besides, noise and quantization errors are often …
world scenes due to sensor constraints. Besides, noise and quantization errors are often …
Learning event guided high dynamic range video reconstruction
Limited by the trade-off between frame rate and exposure time when capturing moving
scenes with conventional cameras, frame based HDR video reconstruction suffers from …
scenes with conventional cameras, frame based HDR video reconstruction suffers from …