This paper addresses the problem of 3D human pose estimation in the wild. A significant challenge is the lack of training data, i.e., 2D images of humans annotated with 3D poses. Such data is necessary to train state-of-the-art CNN architectures. Here, we propose a solution to generate a large set of photorealistic synthetic images of humans with 3D pose annotations. We introduce an image-based...

Based on many large data set, we calibrate a nearoptimal heuristic as a constant function for guiding efficiently A or A∗ algorithm. We claim that this magic number exists as a universal constant for several kinds of date sets. This is perhaps related to the nature of their data sets though it is not theoretically analyzed yet. In general, A∗ and Dijkstra algorithms always pick up the optimal (...

The paper sets forth in detail categorically-algebraic or catalg foundations for the operations of taking the image and preimage of (fuzzy) sets called forward and backward powerset operators. Motivated by an open question of S. E. Rodabaugh, we construct a monad on the category of sets, the algebras of which generate the fixed-basis forward powerset operator of L. A. Zadeh. On the next step, w...