Localization with Sampling-Argmax Supplementary material

Each mini-batch consists of half 2D and half 3D samples. S7, S8) are used for training and two subjects (S9, S11) for evaluation. The output of the last layer is a per-point probability map for each keypoint. Furthermore, our method is an improvement of existing capabilities but does not introduce a radically new capability in machine learning. Theoretically, the underlying density function cannot be perfectly reconstructed since the proposed basis distributions are fixed.