12 papers
ProDyGS: Dynamic Gaussian Splatting from a Single Static Monocular Camera
Ugo Leone Cavalcanti, Fabio Tosi, Matteo Poggi +4
We present ProDyGS, a novel dynamic 3D Gaussian Splatting framework for high-quality novel view synthesis from videos captured by a single static camera. While existing methods rel…
ToF-Splatting: Dense SLAM using Sparse Time-of-Flight Depth and Multi-Frame Integration
Andrea Conti, Matteo Poggi, Valerio Cambareri +2
Time-of-Flight (ToF) sensors provide efficient active depth sensing at relatively low power budgets; among such designs, only very sparse measurements from low-resolution sensors a…
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…
Revisiting Depth Completion from a Stereo Matching Perspective for Cross-domain Generalization
Luca Bartolomei, Matteo Poggi, Andrea Conti +2
This paper proposes a new framework for depth completion robust against domain-shifting issues. It exploits the generalization capability of modern stereo networks to face depth co…
Active Stereo Without Pattern Projector
Luca Bartolomei, Matteo Poggi, Fabio Tosi +2
This paper proposes a novel framework integrating the principles of active stereo in standard passive camera systems without a physical pattern projector. We virtually project a pa…
Sparsity Agnostic Depth Completion
Andrea Conti, Matteo Poggi, Stefano Mattoccia
We present a novel depth completion approach agnostic to the sparsity of depth points, that is very likely to vary in many practical applications. State-of-the-art approaches yield…
Multi-View Guided Multi-View Stereo
Matteo Poggi, Andrea Conti, Stefano Mattoccia
This paper introduces a novel deep framework for dense 3D reconstruction from multiple image frames, leveraging a sparse set of depth measurements gathered jointly with image acqui…
Unsupervised confidence for LiDAR depth maps and applications
Andrea Conti, Matteo Poggi, Filippo Aleotti +1
Depth perception is pivotal in many fields, such as robotics and autonomous driving, to name a few. Consequently, depth sensors such as LiDARs rapidly spread in many applications.…
Monitoring social distancing with single image depth estimation
Alessio Mingozzi, Andrea Conti, Filippo Aleotti +2
The recent pandemic emergency raised many challenges regarding the countermeasures aimed at containing the virus spread, and constraining the minimum distance between people result…