9 citations · 11 across the 17 of their papers we have counts for
18 papers
DAPEVO: Deep Adaptive Patch Frame-Event Visual Odometry
Luca Gandolfi, Simone Nascivera, Roberto Pellerito +3
Visual odometry is essential for autonomous navigation in GPS-denied environments, yet RGB-based methods remain vulnerable to motion blur, challenging illumination, and dropped fra…
Why does Deep Learning Improve Visual SLAM?
Giovanni Cioffi, Davide Scaramuzza
Visual SLAM is a well-established technology utilized in a wide range of real-world applications. However, its performance still degrades under challenging visual conditions, such…
Generative Event Pretraining with Foundation Model Alignment
Jianwen Cao, Jiaxu Xing, Nico Messikommer +1
Event cameras provide robust visual signals under fast motion and challenging illumination conditions thanks to their microsecond latency and high dynamic range. However, their uni…
Event-Aided Sharp Radiance Field Reconstruction for Fast-Flying Drones
Rong Zou, Marco Cannici, Davide Scaramuzza
Fast-flying aerial robots promise rapid inspection under limited battery constraints, with direct applications in infrastructure inspection, terrain exploration, and search and res…
Motion-aware Event Suppression for Event Cameras
Roberto Pellerito, Nico Messikommer, Giovanni Cioffi +2
Event cameras report asynchronously per-pixel brightness changes with microsecond latency, encoding dynamic visual information as a sparse stream of events. However, their extreme…
Event-Based De-Snowing for Autonomous Driving
Manasi Muglikar, Nico Messikommer, Marco Cannici +1
Adverse weather conditions, particularly heavy snowfall, pose significant challenges to both human drivers and autonomous vehicles. Traditional image-based de-snowing methods often…
Egocentric Event-Based Vision for Ping Pong Ball Trajectory Prediction
Ivan Alberico, Marco Cannici, Giovanni Cioffi +1
In this paper, we present a real-time egocentric trajectory prediction system for table tennis using event cameras. Unlike standard cameras, which suffer from high latency and moti…
Reading in the Dark with Foveated Event Vision
Carl Brander, Giovanni Cioffi, Nico Messikommer +1
Current smart glasses equipped with RGB cameras struggle to perceive the environment in low-light and high-speed motion scenarios due to motion blur and the limited dynamic range o…
Perturbed State Space Feature Encoders for Optical Flow with Event Cameras
Gokul Raju Govinda Raju, Nikola Zubić, Marco Cannici +1
With their motion-responsive nature, event-based cameras offer significant advantages over traditional cameras for optical flow estimation. While deep learning has improved upon tr…
LiDAR Registration with Visual Foundation Models
Niclas Vödisch, Giovanni Cioffi, Marco Cannici +2
LiDAR registration is a fundamental task in robotic mapping and localization. A critical component of aligning two point clouds is identifying robust point correspondences using po…
GEM: A Generalizable Ego-Vision Multimodal World Model for Fine-Grained Ego-Motion, Object Dynamics, and Scene Composition Control
Mariam Hassan, Sebastian Stapf, Ahmad Rahimi +17
We present GEM, a Generalizable Ego-vision Multimodal world model that predicts future frames using a reference frame, sparse features, human poses, and ego-trajectories. Hence, ou…
Monocular Event-Based Vision for Obstacle Avoidance with a Quadrotor
Anish Bhattacharya, Marco Cannici, Nishanth Rao +4
We present the first static-obstacle avoidance method for quadrotors using just an onboard, monocular event camera. Quadrotors are capable of fast and agile flight in cluttered env…
FaVoR: Features via Voxel Rendering for Camera Relocalization
Vincenzo Polizzi, Marco Cannici, Davide Scaramuzza +1
Camera relocalization methods range from dense image alignment to direct camera pose regression from a query image. Among these, sparse feature matching stands out as an efficient,…
3D scene generation from scene graphs and self-attention
Pietro Bonazzi, Mengqi Wang, Diego Martin Arroyo +4
Synthesizing realistic and diverse indoor 3D scene layouts in a controllable fashion opens up applications in simulated navigation and virtual reality. As concise and robust repres…
Few-shot point cloud reconstruction and denoising via learned Guassian splats renderings and fine-tuned diffusion features
Pietro Bonazzi, Marie-Julie Rakatosaona, Marco Cannici +2
Existing deep learning methods for the reconstruction and denoising of point clouds rely on small datasets of 3D shapes. We circumvent the problem by leveraging deep learning metho…
An N-Point Linear Solver for Line and Motion Estimation with Event Cameras
Ling Gao, Daniel Gehrig, Hang Su +2
Event cameras respond primarily to edges--formed by strong gradients--and are thus particularly well-suited for line-based motion estimation. Recent work has shown that events gene…
Mitigating Motion Blur in Neural Radiance Fields with Events and Frames
Marco Cannici, Davide Scaramuzza
Neural Radiance Fields (NeRFs) have shown great potential in novel view synthesis. However, they struggle to render sharp images when the data used for training is affected by moti…
Deep Visual Odometry with Events and Frames
Roberto Pellerito, Marco Cannici, Daniel Gehrig +4
Visual Odometry (VO) is crucial for autonomous robotic navigation, especially in GPS-denied environments like planetary terrains. To improve robustness, recent model-based VO syste…