13 citations · 14 across the 4 of their papers we have counts for
4 papers
LiFT: Lightweight, FPGA-tailored 3D object detection based on LiDAR data
Konrad Lis, Tomasz Kryjak, Marek Gorgon
This paper presents LiFT, a lightweight, fully quantized 3D object detection algorithm for LiDAR data, optimized for real-time inference on FPGA platforms. Through an in-depth anal…
Comparative study of subset selection methods for rapid prototyping of 3D object detection algorithms
Konrad Lis, Tomasz Kryjak
Object detection in 3D is a crucial aspect in the context of autonomous vehicles and drones. However, prototyping detection algorithms is time-consuming and costly in terms of ener…
PointPillars Backbone Type Selection For Fast and Accurate LiDAR Object Detection
Konrad Lis, Tomasz Kryjak
3D object detection from LiDAR sensor data is an important topic in the context of autonomous cars and drones. In this paper, we present the results of experiments on the impact of…
Optimisation of the PointPillars network for 3D object detection in point clouds
Joanna Stanisz, Konrad Lis, Tomasz Kryjak +1
In this paper we present our research on the optimisation of a deep neural network for 3D object detection in a point cloud. Techniques like quantisation and pruning available in t…