Alessio Palma

The target duration of a synthesized human motion is a critical attribute that requires modeling control over the motion dynamics and style. Speeding up an action performance is not merely fast-forwarding it. However, state-of-the-art techniques for human behavior synthesis have limited control over the target sequence length. We introduce the problem of generating length-aware 3D human motion sequences from textual descriptors, and we propose a novel model to synthesize motions of variable target lengths, which we dub "Length-Aware Latent Diffusion" (LADiff). LADiff consists of two new modules: 1) a length-aware variational auto-encoder to learn motion representations with length-dependent latent codes; 2) a length-conforming latent diffusion model to generate motions with a richness of details that increases with the required target sequence length. LADiff significantly improves over the state-of-the-art across most of the existing motion synthesis metrics on the two established benchmarks of HumanML3D and KIT-ML.

VQAsk is an Android application that helps visually impaired users to get information about images framed by their smartphones. It enables to interact with one’s photographs or the surrounding visual environment through a question-and-answer interface integrating three modalities: speech interaction, haptic feedback that facilitates navigation and interaction, and sight. VQAsk is primarily designed to help visually impaired users mentally visualize what they cannot see, but it can also accommodate users with varying levels of visual ability. To this aim, it embeds advanced NLP and Computer Vision techniques to answer all user questions about the image on the cell screen. Image processing is enhanced by background removal through advanced segmentation models that identify important image elements. The outcomes of a testing phase confirmed the importance of this project as a first attempt at using AI-supported multimodality to enhance visually impaired users’ experience.