81 citations · 457 across the 71 of their papers we have counts for
90 papers · 1 filter
MicroISP: Processing 32MP Photos on Mobile Devices with Deep Learning
Andrey Ignatov, Anastasia Sycheva, Radu Timofte +8
While neural networks-based photo processing solutions can provide a better image quality compared to the traditional ISP systems, their application to mobile devices is still very…
PyNet-V2 Mobile: Efficient On-Device Photo Processing With Neural Networks
Andrey Ignatov, Grigory Malivenko, Radu Timofte +8
The increased importance of mobile photography created a need for fast and performant RAW image processing pipelines capable of producing good visual results in spite of the mobile…
Efficient Single-Image Depth Estimation on Mobile Devices, Mobile AI & AIM 2022 Challenge: Report
Andrey Ignatov, Grigory Malivenko, Radu Timofte +36
Various depth estimation models are now widely used on many mobile and IoT devices for image segmentation, bokeh effect rendering, object tracking and many other mobile tasks. Thus…
Learned Smartphone ISP on Mobile GPUs with Deep Learning, Mobile AI & AIM 2022 Challenge: Report
Andrey Ignatov, Radu Timofte, Shuai Liu +35
The role of mobile cameras increased dramatically over the past few years, leading to more and more research in automatic image quality enhancement and RAW photo processing. In thi…
AIM 2022 Challenge on Instagram Filter Removal: Methods and Results
Furkan Kınlı, Sami Menteş, Barış Özcan +30
This paper introduces the methods and the results of AIM 2022 challenge on Instagram Filter Removal. Social media filters transform the images by consecutive non-linear operations,…
SiNeRF: Sinusoidal Neural Radiance Fields for Joint Pose Estimation and Scene Reconstruction
Yitong Xia, Hao Tang, Radu Timofte +1
NeRFmm is the Neural Radiance Fields (NeRF) that deal with Joint Optimization tasks, i.e., reconstructing real-world scenes and registering camera parameters simultaneously. Despit…