Jul 21, 2016 · We propose a novel appearance-based Object Detection system that is able to detect obstacles at very long range and at a very high speed (~300Hz),

This work proposes a novel appearance-based Object Detection system that is able to detect obstacles at very long range and at a very high speed (~ 300Hz)

Abstract—Obstacle Detection is a central problem for any robotic system, and critical for autonomous systems that travel at high speeds in unpredictable ...

Ref. [27] adopted fully convolutional network and optical flow as auxiliary information to achieve depth estimation of the occluded areas in the image.Liu et al ...

Monocular Depth Estimation is the task of estimating the depth value (distance relative to the camera) of each pixel given a single (monocular) RGB image.

Monocular Depth Estimation is the task of estimating the depth value (distance relative to the camera) of each pixel given a single (monocular) RGB image.

We propose a fully convolutional network fed with both images and optical flows to obtain fast and robust depth estimation, with a robotic applications-oriented ...

Fast robust monocular depth estimation for obstacle detection with fully convolutional networks. M Mancini, G Costante, P Valigi, TA Ciarfuglia. 2016 IEEE/RSJ ...

Fast Robust Monocular Depth Estimation for Obstacle Detection with Fully Convolutional Networks · Parse Geometry from a Line: Monocular Depth Estimation with ...

Fast robust monocular depth estimation for obstacle detection with fully convolutional networks‏. M Mancini, G Costante, P Valigi, TA Ciarfuglia‏. 2016 IEEE ...