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In the current deep learning paradigm, the amount and quality of training data are as critical as the network architecture and its training details. However, collecting, processing, and annotating real data at scale is difficult, expensive, and time-consum ...
Non-Rigid Structure-from-Motion (NRSfM) reconstructs a deformable 3D object from keypoint correspondences established between monocular 2D images. Current NRSfM methods lack statistical robustness, which is the ability to cope with correspondence errors. T ...
We address the problem of segmenting anomalies and unusual obstacles in road scenes for the purpose of self-driving safety.The objects in question are not present in the common training sets as it is not feasible to collect and annotate examples for every ...
To obtain a more complete understanding of material microstructure at the nanoscale and to gain profound insights into their properties, there is a growing need for more efficient and precise methods that can streamline the process of 3D imaging using a tr ...
Stereo confidence estimation aims to estimate the reliability of the estimated disparity by stereo matching. Different from the previous methods that exploit the limited input modality, we present a novel method that estimates confidence map of an initial ...
Monocular and stereo visions are cost-effective solutions for 3D human localization in the context of self-driving cars or social robots. However, they are usually developed independently and have their respective strengths and limitations. We propose a no ...
An innovative photogrammetric pipeline has been developed by INAF-Padova for the processing of the stereo images from the CaSSIS (Colour and Stereo Imaging System) (Thomas et al., 2014). CaSSIS is the multispectral stereo push frame camera on board ExoMars ...
The correlation properties of light provide an outstanding tool to overcome the limitations of traditional imaging techniques. A relevant case is represented by correlation plenoptic imaging (CPI), a quantum-inspired volumetric imaging protocol employing s ...
The focus of our research is to generate controllable photo-realistic images of real-world scenes from existing observations, i.e., the inverse rendering problem. The approaches we focus on are those through neural rendering, utilizing neural network to de ...
We consider the problem of compressing an information source when a correlated one is available as side information only at the decoder side, which is a special case of the distributed source coding problem in information theory. In particular, we consider ...
