We propose a landmark-constrained algorithm, LA-VDM (Landmark Accelerated Vector Diffusion Maps), to accelerate the Vector Diffusion Maps (VDM) framework built upon the Graph Connection Laplacian (GCL), which captures pairwise connection relationships within complex datasets. LA-VDM introduces a novel two-stage normalization that effectively address nonuniform sampling densities in both the data and the landmark sets. Under a manifold model with the frame bundle structure, we show that we can accurately recover the parallel transport with landmark-constrained diffusion from a point cloud, and hence asymptotically LA-VDM converges to the connection Laplacian. The performance and accuracy of LA-VDM are demonstrated through experiments on simulated datasets and an application to nonlocal image denoising.

Technology Robots'Pokémon Go' players have been unknowingly training delivery robots The massive crowdsourcing effort could use real-world to help robots deliver pizza. A woman holds up her cell phone as she plays the Pokémon Go game in Lafayette Park in front of the White House in Washington, DC on July 12, 2016. Breakthroughs, discoveries, and DIY tips sent six days a week. Nearly a decade ago, turned the real world into a digital scavenger hunt, with virtual creatures hiding in plain sight. The early augmented reality smartphone app prompted hundreds of millions of players to wander into parks, parking lots, and even dimly lit alleyways, peering through their phone cameras in search of Pikachus and Charizards that the app superimposed onto their surroundings.

Synthesizing high-fidelity head avatars is a central problem for computer vision and graphics. While head avatar synthesis algorithms have advanced rapidly, the best ones still face great obstacles in real-world scenarios.

Compared toprevious works, our approach can learn landmarks that are more flexible in terms of capturing large changes in viewpoint.

Recent curriculum Reinforcement Learning (RL) has shown notable progress in solving complex tasks by proposing sequences of surrogate tasks. However, the previous approaches often face challenges when they generate curriculum goals in a high-dimensional space.