Valentina Donzella

Orcid: 0000-0002-3408-6135

According to our database1, Valentina Donzella authored at least 40 papers between 2019 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
DriveCtrl: Conditioned Sim-to-Real Driving Video Generation.
CoRR, May, 2026

EdgeLPR: On the Deep Neural Network trade-off between Precision and Performance in LiDAR Place Recognition.
CoRR, May, 2026

Adverse-to-the-eXtreme Panoptic Segmentation: URVIS 2026 Study and Benchmark.
CoRR, April, 2026

AURORA-KITTI: Any-Weather Depth Completion and Denoising in the Wild.
CoRR, March, 2026

Rethinking probabilistic learning for counterfactual low-light image enhancement in robust engineering vision systems.
Knowl. Based Syst., 2026

2025
Polar Perspectives: Evaluating 2-D LiDAR Projections for Robust Place Recognition with Visual Foundation Models.
CoRR, December, 2025

A Survey and New Perspective of Sensing in the Dark for Intelligent Transportation Systems.
IEEE Trans. Intell. Transp. Syst., November, 2025

Occluded nuScenes: A Multi-Sensor Dataset for Evaluating Perception Robustness in Automated Driving.
CoRR, October, 2025

Occluded nuScenes: A Multi-Sensor Dataset for Evaluating Perception Robustness in Automated Driving.
Dataset, October, 2025

A Target-based Multi-LiDAR Multi-Camera Extrinsic Calibration System.
CoRR, July, 2025

REHEARSE-3D: A Multi-modal Emulated Rain Dataset for 3D Point Cloud De-raining.
CoRR, April, 2025

Universal Framework to Evaluate Automotive Perception Sensor Impact on Perception Functions.
CoRR, March, 2025

Robustness of Panoptic Segmentation for Degraded Automotive Cameras Data.
IEEE Trans Autom. Sci. Eng., 2025

Raw Camera Data Object Detectors: An Optimisation for Automotive Video Processing and Transmission.
IEEE Access, 2025

Automotive DNN-Based Object Detection in the Presence of Lens Obstruction and Video Compression.
IEEE Access, 2025

Robustness Requirement Coverage using a Situation Coverage Approach for Vision-based AI Systems.
Proceedings of the 33rd IEEE International Requirements Engineering Conference, 2025

A New Approach for Bayer Adaption Techniques in Compression.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2025

Lightweight RAW Object Detection for Automated Driving.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2025

Real-Time Mitigation of LiDAR Mutual Interference.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2025

Advancing Blink Detection in Driver Monitoring with Improved Eye Landmark Analysis.
Proceedings of the 28th IEEE International Conference on Intelligent Transportation Systems, 2025

Compressing Noisy Bayer Images: Impact on Object Detection in Automotive.
Proceedings of the IEEE International Conference on Vehicular Electronics and Safety, 2025

An Observability-based Targetless system for LiDAR-to-LiDAR Extrinsic Calibration.
Proceedings of the IEEE International Conference on Vehicular Electronics and Safety, 2025

A Case Study: Evaluating the Impact of LiDAR Integration within the Vehicle Front End.
Proceedings of the IEEE International Conference on Vehicular Electronics and Safety, 2025

Evaluating the Impact of Weather-Induced Sensor Occlusion on BEVFusion for 3D Object Detection.
Proceedings of the IEEE International Conference on Vehicular Electronics and Safety, 2025

2024
Taming Transformers for Realistic Lidar Point Cloud Generation.
CoRR, 2024

Benchmarking the Robustness of Panoptic Segmentation for Automated Driving.
CoRR, 2024

A Novel Score-Based LiDAR Point Cloud Degradation Analysis Method.
IEEE Access, 2024

Exploring Generative AI for Sim2Real in Driving Data Synthesis.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2024

REHEARSE: adveRse wEatHEr datAset for sensoRy noiSe modEls.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2024

Influence of AVC and HEVC compression on detection of vehicles through Faster R-CNN.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2024

Darwick: A Paired Dataset in Low-Light Driving Scenarios for Advanced Perceptual Enhancement and Benchmarking Assessment.
Proceedings of the 27th IEEE International Conference on Intelligent Transportation Systems, 2024

Parametric Physics-Based Snow Model for Automotive Cameras.
Proceedings of the 2024 IEEE SENSORS, Kobe, Japan, October 20-23, 2024, 2024

2023
Accelerating Stereo Image Simulation for Automotive Applications Using Neural Stereo Super Resolution.
IEEE Trans. Intell. Transp. Syst., November, 2023

Semantic-Aware Video Compression for Automotive Cameras.
IEEE Trans. Intell. Veh., June, 2023

Contrastive Learning-Based Framework for Sim-to-Real Mapping of Lidar Point Clouds in Autonomous Driving Systems.
CoRR, 2023

Enhanced Object Detection by Integrating Camera Parameters into Raw Image-Based Faster R-CNN.
Proceedings of the 26th IEEE International Conference on Intelligent Transportation Systems, 2023

The Effect of Camera Data Degradation Factors on Panoptic Segmentation for Automated Driving.
Proceedings of the 26th IEEE International Conference on Intelligent Transportation Systems, 2023

2022
A Two-stage H.264 based Video Compression Method for Automotive Cameras.
Proceedings of the 5th IEEE International Conference on Industrial Cyber-Physical Systems, 2022

2021
The data conundrum: compression of automotive imaging data and deep neural network based perception.
Proceedings of the London Imaging Meeting 2021: Imaging for Deep Learning, 2021

2019
Advances in Silicon Photonic Sensors Using Sub-Wavelength Gratings.
Proceedings of the 2019 24th OptoElectronics and Communications Conference (OECC) and 2019 International Conference on Photonics in Switching and Computing (PSC), 2019


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