68 citations · 118 across the 10 of their papers we have counts for
10 papers
Efficient View Synthesis and 3D-based Multi-Frame Denoising with Multiplane Feature Representations
Thomas Tanay, Aleš Leonardis, Matteo Maggioni
While current multi-frame restoration methods combine information from multiple input images using 2D alignment techniques, recent advances in novel view synthesis are paving the w…
Tunable Convolutions with Parametric Multi-Loss Optimization
Matteo Maggioni, Thomas Tanay, Francesca Babiloni +2
Behavior of neural networks is irremediably determined by the specific loss and data used during training. However it is often desirable to tune the model at inference time based o…
Model-Based Image Signal Processors via Learnable Dictionaries
Marcos V. Conde, Steven McDonagh, Matteo Maggioni +2
Digital cameras transform sensor RAW readings into RGB images by means of their Image Signal Processor (ISP). Computational photography tasks such as image denoising and colour con…
Residual Contrastive Learning for Image Reconstruction: Learning Transferable Representations from Noisy Images
Nanqing Dong, Matteo Maggioni, Yongxin Yang +3
This paper is concerned with contrastive learning (CL) for low-level image restoration and enhancement tasks. We propose a new label-efficient learning paradigm based on residuals,…
Fast Camera Image Denoising on Mobile GPUs with Deep Learning, Mobile AI 2021 Challenge: Report
Andrey Ignatov, Kim Byeoung-su, Radu Timofte +29
Image denoising is one of the most critical problems in mobile photo processing. While many solutions have been proposed for this task, they are usually working with synthetic data…
NTIRE 2021 Challenge on Quality Enhancement of Compressed Video: Methods and Results
Ren Yang, Radu Timofte, Jing Liu +69
This paper reviews the first NTIRE challenge on quality enhancement of compressed video, with a focus on the proposed methods and results. In this challenge, the new Large-scale Di…
Efficient Multi-Stage Video Denoising with Recurrent Spatio-Temporal Fusion
Matteo Maggioni, Yibin Huang, Cheng Li +3
In recent years, denoising methods based on deep learning have achieved unparalleled performance at the cost of large computational complexity. In this work, we propose an Efficien…
Diagnosing and Preventing Instabilities in Recurrent Video Processing
Thomas Tanay, Aivar Sootla, Matteo Maggioni +4
Recurrent models are a popular choice for video enhancement tasks such as video denoising or super-resolution. In this work, we focus on their stability as dynamical systems and sh…
NTIRE 2020 Challenge on Real Image Denoising: Dataset, Methods and Results
Abdelrahman Abdelhamed, Mahmoud Afifi, Radu Timofte +87
This paper reviews the NTIRE 2020 challenge on real image denoising with focus on the newly introduced dataset, the proposed methods and their results. The challenge is a new versi…
Pixel Adaptive Filtering Units
Filippos Kokkinos, Ioannis Marras, Matteo Maggioni +2
State-of-the-art methods for computer vision rely heavily on the translation equivariance and spatial sharing properties of convolutional layers without explicitly taking into cons…