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20202025
most citedEvent-based vision on FPGAs -- a survey

17 citations · 122 across the 28 of their papers we have counts for

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30 papers · 1 filter

cs.CV2025★ 5 cited

Interpolation-Based Event Visual Data Filtering Algorithms

Marcin Kowlaczyk, Tomasz Kryjak

The field of neuromorphic vision is developing rapidly, and event cameras are finding their way into more and more applications. However, the data stream from these sensors is char…

cs.CV2025

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…

cs.CV2024

Increasing the scalability of graph convolution for FPGA-implemented event-based vision

Piotr Wzorek, Kamil Jeziorek, Tomasz Kryjak +1

Event cameras are becoming increasingly popular as an alternative to traditional frame-based vision sensors, especially in mobile robotics. Taking full advantage of their high temp…

cs.CV2024★ 17 cited

Event-based vision on FPGAs -- a survey

Tomasz Kryjak

In recent years there has been a growing interest in event cameras, i.e. vision sensors that record changes in illumination independently for each pixel. This type of operation ens…

cs.CV2024★ 3 cited

PowerYOLO: Mixed Precision Model for Hardware Efficient Object Detection with Event Data

Dominika Przewlocka-Rus, Tomasz Kryjak, Marek Gorgon

The performance of object detection systems in automotive solutions must be as high as possible, with minimal response time and, due to the often battery-powered operation, low ene…

cs.CV2024★ 8 cited

Embedded Graph Convolutional Networks for Real-Time Event Data Processing on SoC FPGAs

Kamil Jeziorek, Piotr Wzorek, Krzysztof Blachut +2

The utilisation of event cameras represents an important and swiftly evolving trend aimed at addressing the constraints of traditional video systems. Particularly within the automo…