Aniello Panariello

Aniello Panariello

PhD Student in Artificial Intelligence

AImageLab @ University of Modena and Reggio Emilia

About Me

I am Aniello Panariello, a Ph.D. student affiliated with the AImageLab research group at the University of Modena and Reggio Emilia, under the guidance of Prof. Simone Calderara, I am immersed in exploring Computer Vision and Deep Learning techniques. My prior experience includes leading the Computer Division for the Formula Student Team - MMR Driverless, where I focused on enhancing the perception capabilities of an autonomous racing car.

Two primary focal points characterize my research journey. The first centers around Monocular Distance Estimation, a challenging area where I explore methods to accurately gauge distances using single-camera inputs. The second area of my research revolves around Video Anomaly Detection, a field focused on identifying unusual human activities within video clips. In both domains, I employ innovative unsupervised and weakly supervised methods to maximize the utility of limited annotations while contributing to advancing these cutting-edge technologies.

Feel free to reach me for any question or curiosity.

  • Computer Vision
  • Machine Learning
  • Deep Learning
  • Video Anomaly Detection
  • Self-supervised Learning
  • Continual Learning
  • PhD in Artificial Intelligence, 2025

    University of Modena and Reggio Emilia

  • MS in Artificial Intelligence, 2021

    University of Modena and Reggio Emilia

  • BSc in Computer Engineering, 2019

    University of Salerno


AImageLab @ University of Modena and Reggio Emilia
Research Fellow
Jan 2022 – Oct 2022 Modena, Italy
  • Developed a deep learning based software for the detection of video anomalous activities on public transport for the pan-European project InSecTT.
  • Studied and investigated techniques for data imbalance mitigation in anomaly detection problems.
  • Introduced a novel consistency-based regulation loss for temporal anomaly localization in self-supervised learning settings.
  • Developing of new techniques for video anomaly detection and video explaination using VAEs.
MMR Driverless - Formula Student Team
Computer Division Leader
Nov 2019 – Jul 2022 Modena, Italy
  • Construction of a dataset of traffic cones consisting of four classes and 9000 images, with which a neural network has been fine-tuned to perform cones detection in images.
  • Developing of a deep learning based software for autonomous car perception based on cameras and Lidar sensors. The car is able to accurately detect the color and precise distance of traffic cones that define the track, in a 180° FOV ahead.
  • Project manager for the computer division.
Mivia Lab @ University of Salerno
Dec 2018 – Mar 2019 Salerno, Italy
Developed “ARPosture” (Swift) for the thesis work. The app was presented to the head of the Apple Developer Academy, being among the top 5 best apps developed at the University of Salerno in 2017-2019.
Apple Foundation Program @ University of Salerno
iOS App Developer
Jun 2018 – Jul 2018 Salerno, Italy
  • Participated in the iOS Foundation Program, which improved my team-working, team-leading and app developing skills.
  • Was the lead developer and project manager of the “Kelnero” app (Swift).


Recent Publications

Check my Google Scholar profile for the complete publication list.
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(2023). TrackFlow: Multi-Object tracking with Normalizing Flows. In ICCV'23.

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(2022). Consistency-based Self-supervised Learning for Temporal Anomaly Localization. In ECCVW'22.

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Clean Air
Autmatically keep the internal air quality at its best, with pollution prediction.
Get relative head position and prompt when the user is in a bad posture.