9 citations · 11 across the 17 of their papers we have counts for
7 papers · 1 filter
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…