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Found 5 papers, 1 papers with code
CNN for IMU Assisted Odometry Estimation using Velodyne LiDAR
Our networks show significantly better precision in the estimation of translational motion parameters comparing with state of the art method LOAM, while achieving real-time performance.
Robotics
CNN for Very Fast Ground Segmentation in Velodyne LiDAR Data
This paper presents a novel method for ground segmentation in Velodyne point clouds.
Robotics
Camera Elevation Estimation from a Single Mountain Landscape Photograph
This work addresses the problem of camera elevation estimation from a single photograph in an outdoor environment.
Compression Artifacts Removal Using Convolutional Neural Networks
This paper shows that it is possible to train large and deep convolutional neural networks (CNN) for JPEG compression artifacts reduction, and that such networks can provide significantly better reconstruction quality compared to previously used smaller networks as well as to any other state-of-the-art methods.
CNN for License Plate Motion Deblurring
In this work we explore the previously proposed approach of direct blind deconvolution and denoising with convolutional neural networks in a situation where the blur kernels are partially constrained.
