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
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 …
Generative diffusion prior for unified image restoration and enhancement
Existing image restoration methods mostly leverage the posterior distribution of natural
images. However, they often assume known degradation and also require supervised …
images. However, they often assume known degradation and also require supervised …
Multi-interactive feature learning and a full-time multi-modality benchmark for image fusion and segmentation
Multi-modality image fusion and segmentation play a vital role in autonomous driving and
robotic operation. Early efforts focus on boosting the performance for only one task, eg …
robotic operation. Early efforts focus on boosting the performance for only one task, eg …
Blindly assess image quality in the wild guided by a self-adaptive hyper network
Blind image quality assessment (BIQA) for authentically distorted images has always been a
challenging problem, since images captured in the wild include varies contents and diverse …
challenging problem, since images captured in the wild include varies contents and diverse …
Hdr-nerf: High dynamic range neural radiance fields
Abstract We present High Dynamic Range Neural Radiance Fields (HDR-NeRF) to recover
an HDR radiance field from a set of low dynamic range (LDR) views with different …
an HDR radiance field from a set of low dynamic range (LDR) views with different …
Time lens++: Event-based frame interpolation with parametric non-linear flow and multi-scale fusion
S Tulyakov, A Bochicchio, D Gehrig… - Proceedings of the …, 2022 - openaccess.thecvf.com
Recently, video frame interpolation using a combination of frame-and event-based cameras
has surpassed traditional image-based methods both in terms of performance and memory …
has surpassed traditional image-based methods both in terms of performance and memory …
AI-assisted CT imaging analysis for COVID-19 screening: Building and deploying a medical AI system
The sudden outbreak of novel coronavirus 2019 (COVID-19) increased the diagnostic
burden of radiologists. In the time of an epidemic crisis, we hope artificial intelligence (AI) to …
burden of radiologists. In the time of an epidemic crisis, we hope artificial intelligence (AI) to …
Ghost-free high dynamic range imaging with context-aware transformer
High dynamic range (HDR) deghosting algorithms aim to generate ghost-free HDR images
with realistic details. Restricted by the locality of the receptive field, existing CNN-based …
with realistic details. Restricted by the locality of the receptive field, existing CNN-based …
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 …