Can adversarial networks hallucinate occluded people with a plausible aspect?

When you see a person in a crowd, occluded by other persons, you miss visual information that can be used to recognize, re-identify or simply classify him or her. You can imagine its appearance given your experience, nothing more. Similarly, AI solutions can try to hallucinate missing information with specific deep learning architectures, suitably trained with people with and without occlusions. The goal of this work is to generate a complete image of a person, given an occluded version in input, that should be a) without occlusion b) similar at pixel level to a completely visible people shape c) capable to conserve similar visual attributes (e.g. male/female) of the original one. For the purpose, we propose a new approach by integrating the state-of-the-art of neural network architectures, namely U-nets and GANs, as well as discriminative attribute classification nets, with an architecture specifically designed to de-occlude people shapes. The network is trained to optimize a Loss function which could take into account the aforementioned objectives. As well we propose two datasets for testing our solution: the first one, occluded RAP, created automatically by occluding real shapes of the RAP dataset created by Li et al. (2016) (which collects also attributes of the people aspect); the second is a large synthetic dataset, AiC, generated in computer graphics with data extracted from the GTA video game, that contains 3D data of occluded objects by construction. Results are impressive and outperform any other previous proposal. This result could be an initial step to many further researches to recognize people and their behavior in an open crowded world

Preliminary evidence on the role of vestibolo- and neo-cerebellar circuits in the consolidation of spatial memory related to navigation.

To evaluate if the cerebellum takes part in the process of consolidation of the memory traces related to navigation, we tested in a Morris water maze two groups of male rats, chronically implanted for injection into the cerebellar nuclei of saline or muscimol (MU), a GABAA agonist with a transient inhibitory action. During the acquisition phase (Place test) animals were trained to find a submerged escape platform by the use of distal cues in a protocol of 8 trials/day (2 blocks of 4 trials) for 5 days, and injected immediately after. A Probe test was applied before Place test; the time spent in the area where the platform was previously located is an index of consolidation.Based on histology, MU-treated animals were sorted in: (a) dorsal dentate group (DDN) and (b) ventromedial dentate group (VMDN), in which the injected drug reached also the vestibular nuclei. In the place test, the VMDN showed versus controls (C), longer latencies in reaching the platform in the first block of each day, indicating a less efficient retention. In the probe test, C and DDN showed a gradual increase of time spent in reference quadrant up to values around 40% at day 4 while the VMDN remained around the value of 25 %, regarded as casual distribution. Results seem to exclude a role of the cerebellum trough the dentate nucleus in the process of spatial memory consolidation, at least at the time span of our protocol, and suggest that such a role could be exerted trough the vestibular system