Three-dimensional (3D) modeling of non-linear objects from stylized sketches is a challenge even for computer graphics experts. The extrapolation of object parameters from a stylized sketch is a very complex and cumbersome task. In the present study, we propose a broker system that can transform a stylized sketch of a tree into a complete 3D model by mediating between a modeler and a 3D modeling software. The input sketches do not need to be accurate or detailed: They must only contain a rudimentary outline of the tree that the modeler wishes to 3D model. Our approach is based on a well-defined Deep Neural Network architecture, called TreeSketchNet (TSN), based on convolutions and capable of generating Weber and Penn [1995] parameters from a simple sketch of a tree. These parameters are then interpreted by the modeling software, which generates the 3D model of the tree pictured in the sketch. The training dataset consists of synthetically generated sketches that are associated with Weber–Penn parameters, generated by a dedicated Blender modeling software add-on. The accuracy of the proposed method is demonstrated by testing the TSN with synthetic and hand-made sketches. Finally, we provide a qualitative analysis of our results, by evaluating the coherence of the predicted parameters with several distinguishing features.

In recent years, extended reality has increasingly been used to enhance the shopping experience for customers. In particular, some virtual dressing room applications have begun to develop, as they allow customers to try on digital clothes and see how they fit. However, recent studies found that the presence of an AI or a real shopping assistant could improve the virtual dressing room experience. In response to this, we have developed a collaborative synchronous virtual dressing room for image consulting that allows customers to try on realistic digital garments chosen by a remotely connected human image consultant. The application has different features for the image consultant and the customer. The image consultant can connect to the application, define a database of garments, select different outfits with different sizes for the customer to try, and communicate with the customer through a single RGB camera system. The customer-side application can visualize the description of the outfit that the avatar is wearing, as well as the virtual shopping cart. The main purpose of the application is to offer an immersive experience, ensured by the presence of a realistic environment, an avatar that resembles the customer, a real-time physically-based cloth simulation algorithm, and a video-chat system.

The COVID-19 pandemic has underscored the need for real-time, collaborative virtual tools to support remote activities across various domains, including education and cultural heritage. Virtual walkthroughs provide a potent means of exploring, learning about, and interacting with historical sites worldwide. Nonetheless, creating realistic and user-friendly applications poses a significant challenge. This study investigates the potential of collaborative virtual walkthroughs as an educational tool for cultural heritage sites, with a focus on the Sassi of Matera, a UNESCO World Heritage Site in Italy. The virtual walkthrough application, developed using RealityCapture and Unreal Engine, leveraged photogrammetric reconstruction and deep learning-based hand gesture recognition to offer an immersive and accessible experience, allowing users to interact with the virtual environment using intuitive gestures. A test with 36 participants resulted in positive feedback regarding the application’s effectiveness, intuitiveness, and user-friendliness. The findings suggest that virtual walkthroughs can provide precise representations of complex historical locations, promoting tangible and intangible aspects of heritage. Future work should focus on expanding the reconstructed site, enhancing the performance, and assessing the impact on learning outcomes. Overall, this study highlights the potential of virtual walkthrough applications as a valuable resource for architecture, cultural heritage, and environmental education.