4 papers · 1 filter
Marigold V2: Revisiting Diffusion Transformers for Monocular Depth Estimation
Igor Pavlovic, Thiemo Wandel, Anton Obukhov +6
Monocular depth estimation is a ubiquitous yet highly ill-posed computer vision task, with downstream applications in scene reconstruction, computational photography, and robotics,…
ZipDepth: Bringing Lightweight Zero-Shot Monocular Depth Anywhere, on Any Device
Fabio Tosi, Luca Bartolomei, Matteo Poggi +1
Monocular depth estimation has seen remarkable progress through foundation models achieving robust zero-shot generalization, yet their computational demands place them far beyond t…
Bidirectional Cross-Modal Prompting for Event-Frame Asymmetric Stereo
Ninghui Xu, Fabio Tosi, Lihui Wang +5
Conventional frame-based cameras capture rich contextual information but suffer from limited temporal resolution and motion blur in dynamic scenes. Event cameras offer an alternati…
EventHub: Data Factory for Generalizable Event-Based Stereo Networks without Active Sensors
Luca Bartolomei, Fabio Tosi, Matteo Poggi +2
We propose EventHub, a novel framework for training deep-event stereo networks without ground truth annotations from costly active sensors, relying instead on standard color images…