4 citations · 4 across the 2 of their papers we have counts for
5 papers
Gated3D: Monocular 3D Object Detection From Temporal Illumination Cues
Frank Julca-Aguilar, Jason Taylor, Mario Bijelic +3
Today's state-of-the-art methods for 3D object detection are based on lidar, stereo, or monocular cameras. Lidar-based methods achieve the best accuracy, but have a large footprint…
Gated2Depth: Real-time Dense Lidar from Gated Images
Tobias Gruber, Frank Julca-Aguilar, Mario Bijelic +3
We present an imaging framework which converts three images from a gated camera into high-resolution depth maps with depth accuracy comparable to pulsed lidar measurements. Existin…
Symbol detection in online handwritten graphics using Faster R-CNN
Frank D. Julca-Aguilar, Nina S. T. Hirata
Symbol detection techniques in online handwritten graphics (e.g. diagrams and mathematical expressions) consist of methods specifically designed for a single graphic type. In this…
Image operator learning coupled with CNN classification and its application to staff line removal
Frank D. Julca-Aguilar, Nina S. T. Hirata
Many image transformations can be modeled by image operators that are characterized by pixel-wise local functions defined on a finite support window. In image operator learning, th…
A General Framework for the Recognition of Online Handwritten Graphics
Frank Julca-Aguilar, Harold Mouchère, Christian Viard-Gaudin +1
We propose a new framework for the recognition of online handwritten graphics. Three main features of the framework are its ability to treat symbol and structural level information…