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Found 6 papers, 2 papers with code
A Semantic Segmentation-guided Approach for Ground-to-Aerial Image Matching
Nowadays the accurate geo-localization of ground-view images has an important role across domains as diverse as journalism, forensics analysis, transports, and Earth Observation.
Learning from Unlabelled Data with Transformers: Domain Adaptation for Semantic Segmentation of High Resolution Aerial Images
In this paper, we develop a new model for semantic segmentation of unlabelled images, the Non-annotated Earth Observation Semantic Segmentation (NEOS) model.
Adversarial Data Poisoning for Fake News Detection: How to Make a Model Misclassify a Target News without Modifying It
Fake news detection models are critical to countering disinformation but can be manipulated through adversarial attacks.
Learning Double-Compression Video Fingerprints Left from Social-Media Platforms
However, fake news and manipulated content can easily go viral, so, being able to verify the source of videos and images as well as to distinguish between native and downloaded content becomes essential.
DepthFake: a depth-based strategy for detecting Deepfake videos
Fake content has grown at an incredible rate over the past few years.
Identification of Social-Media Platform of Videos through the Use of Shared Features
To mitigate this limitation, in this work we propose two different solutions based on transfer learning and multitask learning to determine whether a video has been uploaded from or downloaded to a specific social platform through the use of shared features with images trained on the same task.
