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20212025
most citedA survey on efficient vision transformers: algorithms, techniques, and performance benchmarking

133 citations · 235 across the 17 of their papers we have counts for

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14 papers · 1 filter

cs.CV2025

VidCLearn: A Continual Learning Approach for Text-to-Video Generation

Luca Zanchetta, Lorenzo Papa, Luca Maiano +1

Text-to-video generation is an emerging field in generative AI, enabling the creation of realistic, semantically accurate videos from text prompts. While current models achieve imp…

cs.CV2025

Shedding Light on Depth: Explainability Assessment in Monocular Depth Estimation

Lorenzo Cirillo, Claudio Schiavella, Lorenzo Papa +2

Explainable artificial intelligence is increasingly employed to understand the decision-making process of deep learning models and create trustworthiness in their adoption. However…

cs.CV2025

Enhancing Abnormality Identification: Robust Out-of-Distribution Strategies for Deepfake Detection

Luca Maiano, Fabrizio Casadei, Irene Amerini

Detecting deepfakes has become a critical challenge in Computer Vision and Artificial Intelligence. Despite significant progress in detection techniques, generalizing them to open-…

cs.CV2025

Z-SASLM: Zero-Shot Style-Aligned SLI Blending Latent Manipulation

Alessio Borgi, Luca Maiano, Irene Amerini

We introduce Z-SASLM, a Zero-Shot Style-Aligned SLI (Spherical Linear Interpolation) Blending Latent Manipulation pipeline that overcomes the limitations of current multi-style ble…

cs.CV2025

Enhancing Ground-to-Aerial Image Matching for Visual Misinformation Detection Using Semantic Segmentation

Emanuele Mule, Matteo Pannacci, Ali Ghasemi Goudarzi +4

The recent advancements in generative AI techniques, which have significantly increased the online dissemination of altered images and videos, have raised serious concerns about th…

cs.CV2024★ 19 cited

Continuous fake media detection: adapting deepfake detectors to new generative techniques

Francesco Tassone, Luca Maiano, Irene Amerini

Generative techniques continue to evolve at an impressively high rate, driven by the hype about these technologies. This rapid advancement severely limits the application of deepfa…

cs.CV2024

A Semantic Segmentation-guided Approach for Ground-to-Aerial Image Matching

Francesco Pro, Nikolaos Dionelis, Luca Maiano +2

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. T…

cs.CV2024

Learning from Unlabelled Data with Transformers: Domain Adaptation for Semantic Segmentation of High Resolution Aerial Images

Nikolaos Dionelis, Francesco Pro, Luca Maiano +2

Data from satellites or aerial vehicles are most of the times unlabelled. Annotating such data accurately is difficult, requires expertise, and is costly in terms of time. Even if…

cs.CV2024★ 41 cited

METER: a mobile vision transformer architecture for monocular depth estimation

L. Papa, P. Russo, I. Amerini

Depth estimation is a fundamental knowledge for autonomous systems that need to assess their own state and perceive the surrounding environment. Deep learning algorithms for depth…

cs.CV2024★ 7 cited

D4D: An RGBD diffusion model to boost monocular depth estimation

L. Papa, P. Russo, I. Amerini

Ground-truth RGBD data are fundamental for a wide range of computer vision applications; however, those labeled samples are difficult to collect and time-consuming to produce. A co…

cs.CV2023★ 133 cited

A survey on efficient vision transformers: algorithms, techniques, and performance benchmarking

Lorenzo Papa, Paolo Russo, Irene Amerini +1

Vision Transformer (ViT) architectures are becoming increasingly popular and widely employed to tackle computer vision applications. Their main feature is the capacity to extract g…

cs.CV2022★ 17 cited

Learning Double-Compression Video Fingerprints Left from Social-Media Platforms

Irene Amerini, Aris Anagnostopoulos, Luca Maiano +1

Social media and messaging apps have become major communication platforms. Multimedia contents promote improved user engagement and have thus become a very important communication…

cs.CV2022

DepthFake: a depth-based strategy for detecting Deepfake videos

Luca Maiano, Lorenzo Papa, Ketbjano Vocaj +1

Fake content has grown at an incredible rate over the past few years. The spread of social media and online platforms makes their dissemination on a large scale increasingly access…

cs.CV2021★ 18 cited

Identification of Social-Media Platform of Videos through the Use of Shared Features

Luca Maiano, Irene Amerini, Lorenzo Ricciardi Celsi +1

Videos have become a powerful tool for spreading illegal content such as military propaganda, revenge porn, or bullying through social networks. To counter these illegal activities…