4 papers · 1 filter
Depth on Demand: Streaming Dense Depth from a Low Frame Rate Active Sensor
Andrea Conti, Matteo Poggi, Valerio Cambareri +1
High frame rate and accurate depth estimation plays an important role in several tasks crucial to robotics and automotive perception. To date, this can be achieved through ToF and…
LiDAR-Event Stereo Fusion with Hallucinations
Luca Bartolomei, Matteo Poggi, Andrea Conti +1
Event stereo matching is an emerging technique to estimate depth from neuromorphic cameras; however, events are unlikely to trigger in the absence of motion or the presence of larg…
Active Stereo in the Wild through Virtual Pattern Projection
Luca Bartolomei, Matteo Poggi, Fabio Tosi +2
This paper presents a novel general-purpose guided stereo paradigm that mimics the active stereo principle by replacing the unreliable physical pattern projector with a depth senso…
Range-Agnostic Multi-View Depth Estimation With Keyframe Selection
Andrea Conti, Matteo Poggi, Valerio Cambareri +1
Methods for 3D reconstruction from posed frames require prior knowledge about the scene metric range, usually to recover matching cues along the epipolar lines and narrow the searc…