Search Results for author: Stefano Pini

Found 8 papers, 3 papers with code

Safe Real-World Autonomous Driving by Learning to Predict and Plan with a Mixture of Experts

no code implementations3 Nov 2022 Stefano Pini, Christian S. Perone, Aayush Ahuja, Ana Sofia Rufino Ferreira, Moritz Niendorf, Sergey Zagoruyko

The code for training and testing our model on a public prediction dataset and the video of the road test are available at https://woven. mobi/safepathnet

Autonomous Driving Navigate

CW-ERM: Improving Autonomous Driving Planning with Closed-loop Weighted Empirical Risk Minimization

1 code implementation5 Oct 2022 Eesha Kumar, Yiming Zhang, Stefano Pini, Simon Stent, Ana Ferreira, Sergey Zagoruyko, Christian S. Perone

The imitation learning of self-driving vehicle policies through behavioral cloning is often carried out in an open-loop fashion, ignoring the effect of actions to future states.

Autonomous Driving Imitation Learning

Semi-Perspective Decoupled Heatmaps for 3D Robot Pose Estimation from Depth Maps

no code implementations6 Jul 2022 Alessandro Simoni, Stefano Pini, Guido Borghi, Roberto Vezzani

Knowing the exact 3D location of workers and robots in a collaborative environment enables several real applications, such as the detection of unsafe situations or the study of mutual interactions for statistical and social purposes.

Domain Adaptation Pose Estimation

Multi-Category Mesh Reconstruction From Image Collections

1 code implementation21 Oct 2021 Alessandro Simoni, Stefano Pini, Roberto Vezzani, Rita Cucchiara

Recently, learning frameworks have shown the capability of inferring the accurate shape, pose, and texture of an object from a single RGB image.

M-VAD Names: a Dataset for Video Captioning with Naming

1 code implementation4 Mar 2019 Stefano Pini, Marcella Cornia, Federico Bolelli, Lorenzo Baraldi, Rita Cucchiara

Current movie captioning architectures are not capable of mentioning characters with their proper name, replacing them with a generic "someone" tag.

TAG Video Captioning

Learn to See by Events: Color Frame Synthesis from Event and RGB Cameras

no code implementations5 Dec 2018 Stefano Pini, Guido Borghi, Roberto Vezzani

Event cameras are biologically-inspired sensors that gather the temporal evolution of the scene.

Learning to Generate Facial Depth Maps

no code implementations30 May 2018 Stefano Pini, Filippo Grazioli, Guido Borghi, Roberto Vezzani, Rita Cucchiara

In this paper, an adversarial architecture for facial depth map estimation from monocular intensity images is presented.

Face Verification

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