most citedEfficient High-Resolution Deep Learning: A Survey

7 citations · 9 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20231 cited

Audio-Visual Dataset and Method for Anomaly Detection in Traffic Videos

Błażej Leporowski, Arian Bakhtiarnia, Nicole Bonnici +4

We introduce the first audio-visual dataset for traffic anomaly detection taken from real-world scenes, called MAVAD, with a diverse range of weather and illumination conditions. I…

cs.CV2023

Accurate Gigapixel Crowd Counting by Iterative Zooming and Refinement

Arian Bakhtiarnia, Qi Zhang, Alexandros Iosifidis

The increasing prevalence of gigapixel resolutions has presented new challenges for crowd counting. Such resolutions are far beyond the memory and computation limits of current GPU…

cs.CV20231 cited

PromptMix: Text-to-image diffusion models enhance the performance of lightweight networks

Arian Bakhtiarnia, Qi Zhang, Alexandros Iosifidis

Many deep learning tasks require annotations that are too time consuming for human operators, resulting in small dataset sizes. This is especially true for dense regression problem…

cs.CV2022

Analysis of the Effect of Low-Overhead Lossy Image Compression on the Performance of Visual Crowd Counting for Smart City Applications

Arian Bakhtiarnia, Błażej Leporowski, Lukas Esterle +1

Images and video frames captured by cameras placed throughout smart cities are often transmitted over the network to a server to be processed by deep neural networks for various ta…

cs.CV20227 cited

Efficient High-Resolution Deep Learning: A Survey

Arian Bakhtiarnia, Qi Zhang, Alexandros Iosifidis

Cameras in modern devices such as smartphones, satellites and medical equipment are capable of capturing very high resolution images and videos. Such high-resolution data often nee…