11 accepted papers
vent cameras report asynchronously per-pixel brightness changes with microsecond latency, encoding dynamic visual information as a sparse stream of events. However, their extreme temporal resolution floods perception systems with entangled events from ego-motion and indepen- dently moving objects (I…
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, our model has precise control over object dynamics, ego-agent motion and human poses. GEM generates paired RGB and depth o…
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 point descriptors, which becomes particularly challenging in scenarios involving domain shifts, seasonal changes, and vari…
"Event cameras are neuromorphic image sensors that respond to per-pixel brightness changes, producing a stream of asynchronous and spatially sparse events. Currently, the most successful algorithms for event cameras convert batches of events into dense image-like representations that are synchronous…
Visual Odometry (VO) is crucial for autonomous robotic navigation, especially in GPS-denied environments like planetary terrains. To improve robustness, recent model-based VO systems have begun combining standard and event-based cameras. While event cameras excel in low-light and high-speed motion,…
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 motion blur. On the other hand event cameras excel in dynamic scenes as they measure brightness changes with microsecond reso…
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 environments when piloted manually, but vision-based autonomous flight in unknown environments is difficult in part due to…
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 based on events continues to be an open problem. This is because line feature extraction and dynamics estimation are tightly…
Event cameras are novel bio-inspired sensors, which asynchronously capture pixel-level intensity changes in the form of "events". Due to their sensing mechanism, event cameras have little to no motion blur, a very high temporal resolution and require significantly less power and memory than traditio…
Event cameras are novel bio-inspired sensors, which asynchronously capture pixel-level intensity changes in the form of “events”. The innovative way they acquire data presents several advantages over standard devices, especially in poor lighting and high-speed motion conditions. However, the novelty
Dynamic Vision Sensors (DVSs) asynchronously stream events in correspondence of pixels subject to brightness changes. Differently from classic vision devices, they produce a sparse representation of the scene. Therefore, to apply standard computer vision algorithms, events need to be integrated into…