260 citations · 327 across the 61 of their papers we have counts for
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Geometry meets semantics for semi-supervised monocular depth estimation
Pierluigi Zama Ramirez, Matteo Poggi, Fabio Tosi +2
Depth estimation from a single image represents a very exciting challenge in computer vision. While other image-based depth sensing techniques leverage on the geometry between diff…
Real-time self-adaptive deep stereo
Alessio Tonioni, Fabio Tosi, Matteo Poggi +2
Deep convolutional neural networks trained end-to-end are the state-of-the-art methods to regress dense disparity maps from stereo pairs. These models, however, suffer from a notab…
Learning monocular depth estimation with unsupervised trinocular assumptions
Matteo Poggi, Fabio Tosi, Stefano Mattoccia
Obtaining accurate depth measurements out of a single image represents a fascinating solution to 3D sensing. CNNs led to considerable improvements in this field, and recent trends…
Towards real-time unsupervised monocular depth estimation on CPU
Matteo Poggi, Filippo Aleotti, Fabio Tosi +1
Unsupervised depth estimation from a single image is a very attractive technique with several implications in robotic, autonomous navigation, augmented reality and so on. This topi…