Advancements in virtual reality (VR) technology enable us to rethink the way of interactive 3D modeling - intuitively creating 3D content directly in 3D space. However, conventional VR-based modeling is laborious and tedious to generate a detailed 3D model in full manual mode since users need to carefully draw almost the entire surface. In this paper, we present a freehand mid-air sketching system with the aid of deep learning techniques for modeling structured buildings, where the user freely draws a few key strokes in mid-air using his/her fingers to represent the desired shapes and our system automatically interprets the strokes using a deep neural network and generates a detailed building model based on a procedural modeling method. After creating several building blocks one by one, the user can freely move, rotate, and combine the blocks to form a complex building model. We demonstrate the ease of use for novice users, effectiveness, and efficiency of our sketching system, BuildingSketch, by presenting a variety of building models.

2D sketch-based tree modeling cannot guarantee to generate plausible depth values and full 3D tree shapes. With the advent of virtual reality (VR) technologies, 3D sketching enables a new form for 3D tree modeling. However, it is labor-intensive and difficult to create realistically-looking 3D trees with complicated geometry and lots of detailed twigs with a reasonable amount of effort. In this paper, we explore the use of mid-air finger 3D sketching in VR for tree modeling. We present a hybrid approach that integrates freehand 3D sketches with an automatic population of branch geometries. The user only needs to draw a few 3D strokes in mid-air to define the envelope of the foliage (denoted as lobes) and main branches. Our algorithm then automatically generates a full 3D tree model based on these stroke inputs. Additionally, the shape of the 3D tree model can be modified by freely dragging, squeezing, or moving lobes in mid-air. We demonstrate the ease-of-use, efficiency, and flexibility in tree modeling and overall shape control. We perform user studies and show a variety of realistic tree models generated instantaneously from 3D finger sketching.