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Found 14 papers, 8 papers with code
Transformation Consistency Regularization – A Semi-Supervised Paradigm for Image-to-Image Translation
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.
ColorVideoVDP: A visual difference predictor for image, video and display distortions
ColorVideoVDP is a video and image quality metric that models spatial and temporal aspects of vision, for both luminance and color.
Perceptual Assessment and Optimization of HDR Image Rendering
Existing quality models are mostly designed for low dynamic range (LDR) images, and do not align well with human perception of HDR image quality.
HDR-VDP-3: A multi-metric for predicting image differences, quality and contrast distortions in high dynamic range and regular content
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, prediction of visual differences between a pair of images, or prediction of contrast distortions.
Distilling Style from Image Pairs for Global Forward and Inverse Tone Mapping
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 representing a different style.
How to cheat with metrics in single-image HDR reconstruction
Here, we reproduce a typical evaluation using existing as well as simulated SI-HDR methods to demonstrate how different aspects of the problem affect objective quality metrics.
Training a Task-Specific Image Reconstruction Loss
The choice of a loss function is an important factor when training neural networks for image restoration problems, such as single image super resolution.
Consolidated Dataset and Metrics for High-Dynamic-Range Image Quality
As the existing HDR quality datasets are limited in size, we created a Unified Photometric Image Quality dataset (UPIQ) with over 4, 000 images by realigning and merging existing HDR and standard-dynamic-range (SDR) datasets.
Noise-Aware Merging of High Dynamic Range Image Stacks without Camera Calibration
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.
Transformation Consistency Regularization- A Semi-Supervised Paradigm for Image-to-Image Translation
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.
Hybrid-MST: A Hybrid Active Sampling Strategy for Pairwise Preference Aggregation
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 and noisy pairwise labelling.
A practical guide and software for analysing pairwise comparison experiments
Most popular strategies to capture subjective judgments from humans involve the construction of a unidimensional relative measurement scale, representing order preferences or judgments about a set of objects or conditions.
High Dynamic Range Imaging Technology
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 range of colors than conventional standard dynamic range (SDR) imaging systems.
Langevin Dynamics with Continuous Tempering for Training Deep Neural Networks
Minimizing non-convex and high-dimensional objective functions is challenging, especially when training modern deep neural networks.
