Davide Coccomini

Orcid: 0000-0002-0755-6154

According to our database1, Davide Coccomini authored at least 16 papers between 2019 and 2024.

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

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Cascaded transformer-based networks for wikipedia large-scale image-caption matching.
Multim. Tools Appl., July, 2024

MINTIME: Multi-Identity Size-Invariant Video Deepfake Detection.
IEEE Trans. Inf. Forensics Secur., 2024

Detecting images generated by diffusers.
PeerJ Comput. Sci., 2024

Adversarial Magnification to Deceive Deepfake Detection through Super Resolution.
CoRR, 2024

Deepfake Detection without Deepfakes: Generalization via Synthetic Frequency Patterns Injection.
CoRR, 2024

2023
On the Generalization of Deep Learning Models in Video Deepfake Detection.
J. Imaging, 2023

Deepfake Detection: Challenges and Solutions.
Proceedings of the 31st Symposium of Advanced Database Systems, 2023

Improving Query and Assessment Quality in Text-Based Interactive Video Retrieval Evaluation.
Proceedings of the 2023 ACM International Conference on Multimedia Retrieval, 2023

AIMH Lab Approaches for Deepfake Detection.
Proceedings of the Italia Intelligenza Artificiale, 2023

2022
The Face Deepfake Detection Challenge.
J. Imaging, 2022

Predicting Tornadoes days ahead with Machine Learning.
CoRR, 2022

Transformer-Based Multi-modal Proposal and Re-Rank for Wikipedia Image-Caption Matching.
CoRR, 2022

Cross-Forgery Analysis of Vision Transformers and CNNs for Deepfake Image Detection.
Proceedings of the MAD@ICMR 2022: Proceedings of the 1st International Workshop on Multimedia AI against Disinformation, Newark, NJ, USA, June 27, 2022

Combining EfficientNet and Vision Transformers for Video Deepfake Detection.
Proceedings of the Image Analysis and Processing - ICIAP 2022, 2022

2021
Generative Adversarial Networks for Astronomical Images Generation.
CoRR, 2021

2019
Labeling of Activity Recognition Datasets: Detection of Misbehaving Users.
Proceedings of the Wireless Mobile Communication and Healthcare, 2019


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