14 citations · 16 across the 15 of their papers we have counts for
15 papers
Approximate Imitation Learning for Event-based Quadrotor Flight in Cluttered Environments
Nico Messikommer, Jiaxu Xing, Leonard Bauersfeld +3
Event cameras offer high temporal resolution and low latency, making them ideal sensors for high-speed robotic applications where conventional cameras suffer from motion blur. Howe…
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…
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,…
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…
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…
A 5-Point Minimal Solver for Event Camera Relative Motion Estimation
Ling Gao, Hang Su, Daniel Gehrig +3
Event-based cameras are ideal for line-based motion estimation, since they predominantly respond to edges in the scene. However, accurately determining the camera displacement base…
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…
Revisiting Token Pruning for Object Detection and Instance Segmentation
Yifei Liu, Mathias Gehrig, Nico Messikommer +2
Vision Transformers (ViTs) have shown impressive performance in computer vision, but their high computational cost, quadratic in the number of tokens, limits their adoption in comp…