13 citations · 57 across the 19 of their papers we have counts for
5 papers · 1 filter
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…
An Embarrassingly Simple Approach to Semi-Supervised Few-Shot Learning
Xiu-Shen Wei, He-Yang Xu, Faen Zhang +2
Semi-supervised few-shot learning consists in training a classifier to adapt to new tasks with limited labeled data and a fixed quantity of unlabeled data. Many sophisticated metho…
FasterX: Real-Time Object Detection Based on Edge GPUs for UAV Applications
Wei Zhou, Xuanlin Min, Rui Hu +3
Real-time object detection on Unmanned Aerial Vehicles (UAVs) is a challenging issue due to the limited computing resources of edge GPU devices as Internet of Things (IoT) nodes. T…
Multi Point-Voxel Convolution (MPVConv) for Deep Learning on Point Clouds
Wei Zhou, Xin Cao, Xiaodan Zhang +3
The existing 3D deep learning methods adopt either individual point-based features or local-neighboring voxel-based features, and demonstrate great potential for processing 3D data…
Multi Voxel-Point Neurons Convolution (MVPConv) for Fast and Accurate 3D Deep Learning
Wei Zhou, Xin Cao, Xiaodan Zhang +3
We present a new convolutional neural network, called Multi Voxel-Point Neurons Convolution (MVPConv), for fast and accurate 3D deep learning. The previous works adopt either indiv…