27 citations · 37 across the 7 of their papers we have counts for
4 papers · 1 filter
Hallucinating Dense Optical Flow from Sparse Lidar for Autonomous Vehicles
Victor Vaquero, Alberto Sanfeliu, Francesc Moreno-Noguer
In this paper we propose a novel approach to estimate dense optical flow from sparse lidar data acquired on an autonomous vehicle. This is intended to be used as a drop-in replacem…
Deep Lidar CNN to Understand the Dynamics of Moving Vehicles
Victor Vaquero, Alberto Sanfeliu, Francesc Moreno-Noguer
Perception technologies in Autonomous Driving are experiencing their golden age due to the advances in Deep Learning. Yet, most of these systems rely on the semantically rich infor…
Deconvolutional Networks for Point-Cloud Vehicle Detection and Tracking in Driving Scenarios
Victor Vaquero, Ivan del Pino, Francesc Moreno-Noguer +3
Vehicle detection and tracking is a core ingredient for developing autonomous driving applications in urban scenarios. Recent image-based Deep Learning (DL) techniques are obtainin…
Joint Coarse-And-Fine Reasoning for Deep Optical Flow
Victor Vaquero, German Ros, Francesc Moreno-Noguer +2
We propose a novel representation for dense pixel-wise estimation tasks using CNNs that boosts accuracy and reduces training time, by explicitly exploiting joint coarse-and-fine re…