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Found 8 papers, 6 papers with code
Scaled 360 layouts: Revisiting non-central panoramas
In this work we present a novel approach for 3D layout recovery of indoor environments using single non-central panoramas.
Visual Gyroscope: Combination of Deep Learning Features and Direct Alignment for Panoramic Stabilization
In this article we present a visual gyroscope based on equirectangular panoramas.
Convolution kernel adaptation to calibrated fisheye
Convolution kernels are the basic structural component of convolutional neural networks (CNNs).
Non-central panorama indoor dataset
Omnidirectional images are one of the main sources of information for learning based scene understanding algorithms.
OmniSCV: An Omnidirectional Synthetic Image Generator for Computer Vision
In this paper, we present a tool for generating datasets of omnidirectional images with semantic and depth information.
Atlanta Scaled layouts from non-central panoramas
Our new pipeline aims to extract the boundaries of the structural lines of an indoor environment with a neural network and exploit the properties of non-central projection systems in a new geometrical processing to recover an scaled 3D layout.
Floor extraction and door detection for visually impaired guidance
In this work it is proposed a combination of sensors and algorithms that can lead to the building of a navigation system for visually impaired people.
FreDSNet: Joint Monocular Depth and Semantic Segmentation with Fast Fourier Convolutions
Our experiments show that FreDSNet has similar performance as specific state of the art methods for semantic segmentation and depth estimation.
Ranked #2 on
Depth Estimation
on Stanford2D3D Panoramic
