9 citations · 11 across the 7 of their papers we have counts for
5 papers · 1 filter
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…
Let's take a Walk on Superpixels Graphs: Deformable Linear Objects Segmentation and Model Estimation
Daniele De Gregorio, Gianluca Palli, Luigi Di Stefano
While robotic manipulation of rigid objects is quite straightforward, coping with deformable objects is an open issue. More specifically, tasks like tying a knot, wiring a connecto…
Real-Time RGB-D Camera Pose Estimation in Novel Scenes using a Relocalisation Cascade
Tommaso Cavallari, Stuart Golodetz, Nicholas A. Lord +4
Camera pose estimation is an important problem in computer vision. Common techniques either match the current image against keyframes with known poses, directly regress the pose, o…
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…
A deep learning pipeline for product recognition on store shelves
Alessio Tonioni, Eugenio Serra, Luigi Di Stefano
Recognition of grocery products in store shelves poses peculiar challenges. Firstly, the task mandates the recognition of an extremely high number of different items, in the order…