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Found 22 papers, 4 papers with code
NTIRE 2023 Quality Assessment of Video Enhancement Challenge
61 participating teams submitted their prediction results during the development phase, with a total of 3168 submissions.
A deep scalable neural architecture for soil properties estimation from spectral information
In this paper we propose an adaptive deep neural architecture for the prediction of multiple soil characteristics from the analysis of hyperspectral signatures.
AIM 2022 Challenge on Super-Resolution of Compressed Image and Video: Dataset, Methods and Results
The homepage of this challenge is at https://github. com/RenYang-home/AIM22_CompressSR.
A health telemonitoring platform based on data integration from different sources
The management of people with long-term or chronic illness is one of the biggest challenges for national health systems.
Semi-supervised cross-lingual speech emotion recognition
Performance in Speech Emotion Recognition (SER) on a single language has increased greatly in the last few years thanks to the use of deep learning techniques.
Unsupervised Segmentation of Hyperspectral Remote Sensing Images with Superpixels
In this paper, we propose an unsupervised method for hyperspectral remote sensing image segmentation.
Shallow camera pipeline for night photography rendering
We introduce a camera pipeline for rendering visually pleasing photographs in low light conditions, as part of the NTIRE2022 Night Photography Rendering challenge.
Illumination Estimation Challenge: experience of past two years
The main advantage of testing a method on a challenge over testing in on some of the known datasets is the fact that the ground-truth illuminations for the challenge test images are unknown up until the results have been submitted, which prevents any potential hyperparameter tuning that may be biased.
Spatial Sampling Network for Fast Scene Understanding
We propose a network architecture to perform efficient scene understanding.
Deep Residual Autoencoder for quality independent JPEG restoration
This results is remarkable since the approaches in the state of the art use a different set of weights for each compression quality, while the proposed model uses the same weights for all of them, making it applicable to images in the wild where the QF used for compression is unkwnown.
Multitask Painting Categorization by Deep Multibranch Neural Network
In this work we propose a new deep multibranch neural network to solve the tasks of artist, style, and genre categorization in a multitask formulation.
Learning Illuminant Estimation from Object Recognition
In this paper we present a deep learning method to estimate the illuminant of an image.
Aesthetics Assessment of Images Containing Faces
Recent research has widely explored the problem of aesthetics assessment of images with generic content.
Automated Pruning for Deep Neural Network Compression
In this work we present a method to improve the pruning step of the current state-of-the-art methodology to compress neural networks.
Deep Learning for Logo Recognition
In this paper we propose a method for logo recognition using deep learning.
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On the Use of Deep Learning for Blind Image Quality Assessment
We report on different design choices, ranging from the use of features extracted from pre-trained Convolutional Neural Networks (CNNs) as a generic image description, to the use of features extracted from a CNN fine-tuned for the image quality task.
Single and Multiple Illuminant Estimation Using Convolutional Neural Networks
In this paper we present a method for the estimation of the color of the illuminant in RAW images.
Evaluating color texture descriptors under large variations of controlled lighting conditions
The recognition of color texture under varying lighting conditions is still an open issue.
How Far Can You Get By Combining Change Detection Algorithms?
Given the existence of many change detection algorithms, each with its own peculiarities and strengths, we propose a combination strategy, that we termed IUTIS (In Unity There Is Strength), based on a genetic Programming framework.
Color Constancy Using CNNs
In this work we describe a Convolutional Neural Network (CNN) to accurately predict the scene illumination.
IAT - Image Annotation Tool: Manual
The annotation of image and video data of large datasets is a fundamental task in multimedia information retrieval and computer vision applications.
Remote sensing image classification exploiting multiple kernel learning
Experimental results on publicly available datasets demonstrate the feasibility of the proposed approach.
