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20222025
most citedA survey on efficient vision transformers: algorithms, techniques, and performance benchmarking

133 citations · 188 across the 11 of their papers we have counts for

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7 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 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★ 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

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…