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20162026
most citedDiffDefense: Defending against Adversarial Attacks via Diffusion Models

5 citations · 13 across the 14 of their papers we have counts for

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19 papers · 1 filter

cs.CV2026

Defending from GeoLocalization through Adversarial Road Trips

Niccolò Niccoli, Federico Becattini, Lorenzo Seidenari

Retrieval-based image geolocalization has emerged as a powerful technique for determining the location of a query image by matching it against a large, geotagged database. The succ…

cs.CV2025

Prompt-based Consistent Video Colorization

Silvia Dani, Tiberio Uricchio, Lorenzo Seidenari

Existing video colorization methods struggle with temporal flickering or demand extensive manual input. We propose a novel approach automating high-fidelity video colorization usin…

cs.CV2025

Immunizing Images from Text to Image Editing via Adversarial Cross-Attention

Matteo Trippodo, Federico Becattini, Lorenzo Seidenari

Recent advances in text-based image editing have enabled fine-grained manipulation of visual content guided by natural language. However, such methods are susceptible to adversaria…

cs.CV2024★ 1 cited

Depth-based Privileged Information for Boosting 3D Human Pose Estimation on RGB

Alessandro Simoni, Francesco Marchetti, Guido Borghi +6

Despite the recent advances in computer vision research, estimating the 3D human pose from single RGB images remains a challenging task, as multiple 3D poses can correspond to the…

cs.CV2023

Addressing Limitations of State-Aware Imitation Learning for Autonomous Driving

Luca Cultrera, Federico Becattini, Lorenzo Seidenari +2

Conditional Imitation learning is a common and effective approach to train autonomous driving agents. However, two issues limit the full potential of this approach: (i) the inertia…

cs.CV2023

FLODCAST: Flow and Depth Forecasting via Multimodal Recurrent Architectures

Andrea Ciamarra, Federico Becattini, Lorenzo Seidenari +1

Forecasting motion and spatial positions of objects is of fundamental importance, especially in safety-critical settings such as autonomous driving. In this work, we address the is…