617 citations · 964 across the 17 of their papers we have counts for
20 papers
Robust estimation of exposure ratios in multi-exposure image stacks
Param Hanji, Rafał K. Mantiuk
Merging multi-exposure image stacks into a high dynamic range (HDR) image requires knowledge of accurate exposure times. When exposure times are inaccurate, for example, when they…
HDR-VDP-3: A multi-metric for predicting image differences, quality and contrast distortions in high dynamic range and regular content
Rafal K. Mantiuk, Dounia Hammou, Param Hanji
High-Dynamic-Range Visual-Difference-Predictor version 3, or HDR-VDP-3, is a visual metric that can fulfill several tasks, such as full-reference image/video quality assessment, pr…
Perceptual Quality Assessment of NeRF and Neural View Synthesis Methods for Front-Facing Views
Hanxue Liang, Tianhao Wu, Param Hanji +4
Neural view synthesis (NVS) is one of the most successful techniques for synthesizing free viewpoint videos, capable of achieving high fidelity from only a sparse set of captured i…
Distilling Style from Image Pairs for Global Forward and Inverse Tone Mapping
Aamir Mustafa, Param Hanji, Rafal K. Mantiuk
Many image enhancement or editing operations, such as forward and inverse tone mapping or color grading, do not have a unique solution, but instead a range of solutions, each repre…
G-SemTMO: Tone Mapping with a Trainable Semantic Graph
Abhishek Goswami, Erwan Bernard, Wolf Hauser +2
A Tone Mapping Operator (TMO) is required to render images with a High Dynamic Range (HDR) on media with limited dynamic capabilities. TMOs compress the dynamic range with the aim…
Disentangling Domain and Content
Dan Andrei Iliescu, Aliaksei Mikhailiuk, Damon Wischik +1
Many real-world datasets can be divided into groups according to certain salient features (e.g. grouping images by subject, grouping text by font, etc.). Often, machine learning ta…
How to cheat with metrics in single-image HDR reconstruction
Gabriel Eilertsen, Saghi Hajisharif, Param Hanji +3
Single-image high dynamic range (SI-HDR) reconstruction has recently emerged as a problem well-suited for deep learning methods. Each successive technique demonstrates an improveme…
Training a Task-Specific Image Reconstruction Loss
Aamir Mustafa, Aliaksei Mikhailiuk, Dan Andrei Iliescu +2
The choice of a loss function is an important factor when training neural networks for image restoration problems, such as single image super resolution. The loss function should e…
Consolidated Dataset and Metrics for High-Dynamic-Range Image Quality
Aliaksei Mikhailiuk, Maria Perez-Ortiz, Dingcheng Yue +2
Increasing popularity of high-dynamic-range (HDR) image and video content brings the need for metrics that could predict the severity of image impairments as seen on displays of di…
Noise-Aware Merging of High Dynamic Range Image Stacks without Camera Calibration
Param Hanji, Fangcheng Zhong, Rafal K. Mantiuk
A near-optimal reconstruction of the radiance of a High Dynamic Range scene from an exposure stack can be obtained by modeling the camera noise distribution. The latent radiance is…
Transformation Consistency Regularization- A Semi-Supervised Paradigm for Image-to-Image Translation
Aamir Mustafa, Rafal K. Mantiuk
Scarcity of labeled data has motivated the development of semi-supervised learning methods, which learn from large portions of unlabeled data alongside a few labeled samples. Consi…
Active Sampling for Pairwise Comparisons via Approximate Message Passing and Information Gain Maximization
Aliaksei Mikhailiuk, Clifford Wilmot, Maria Perez-Ortiz +2
Pairwise comparison data arise in many domains with subjective assessment experiments, for example in image and video quality assessment. In these experiments observers are asked t…
Exploiting Synthetically Generated Data with Semi-Supervised Learning for Small and Imbalanced Datasets
Maria Perez-Ortiz, Peter Tino, Rafal Mantiuk +1
Data augmentation is rapidly gaining attention in machine learning. Synthetic data can be generated by simple transformations or through the data distribution. In the latter case,…
Single-frame Regularization for Temporally Stable CNNs
Gabriel Eilertsen, Rafał K. Mantiuk, Jonas Unger
Convolutional neural networks (CNNs) can model complicated non-linear relations between images. However, they are notoriously sensitive to small changes in the input. Most CNNs tra…
Hybrid-MST: A Hybrid Active Sampling Strategy for Pairwise Preference Aggregation
Jing Li, Rafal K. Mantiuk, Junle Wang +2
In this paper we present a hybrid active sampling strategy for pairwise preference aggregation, which aims at recovering the underlying rating of the test candidates from sparse an…
A practical guide and software for analysing pairwise comparison experiments
Maria Perez-Ortiz, Rafal K. Mantiuk
Most popular strategies to capture subjective judgments from humans involve the construction of a unidimensional relative measurement scale, representing order preferences or judgm…
High Dynamic Range Imaging Technology
Alessandro Artusi, Thomas Richter, Touradj Ebrahimi +1
In this lecture note, we describe high dynamic range (HDR) imaging systems; such systems are able to represent luminances of much larger brightness and, typically, also a larger ra…
HDR image reconstruction from a single exposure using deep CNNs
Gabriel Eilertsen, Joel Kronander, Gyorgy Denes +2
Camera sensors can only capture a limited range of luminance simultaneously, and in order to create high dynamic range (HDR) images a set of different exposures are typically combi…
Towards a quality metric for dense light fields
Vamsi Kiran Adhikarla, Marek Vinkler, Denis Sumin +4
Light fields become a popular representation of three dimensional scenes, and there is interest in their processing, resampling, and compression. As those operations often result i…
Langevin Dynamics with Continuous Tempering for Training Deep Neural Networks
Nanyang Ye, Zhanxing Zhu, Rafal K. Mantiuk
Minimizing non-convex and high-dimensional objective functions is challenging, especially when training modern deep neural networks. In this paper, a novel approach is proposed whi…