We present a method for reproducing complex multi-character interactions for physically simulated humanoid characters using deep reinforcement learning.
We present a method for reproducing complex multi-character interactions for physically simulated humanoid characters using deep reinforcement learning.
In this work, we present a fully binarized distance computing (BinDC) framework to perform distance computations for few-shot learning using only accumulation and logic operations.
Recognizing human activities is a decades-old problem in computer vision. With recent advancements in user- assistive augmented reality and virtual reality (AR/VR) systems...
We present the design of a productionized end-to-end stereo depth sensing system that does pre-processing, online stereo rectification, and stereo depth estimation with...
We present the first neural relighting approach for rendering high fidelity personalized hands that can be animated in real-time under novel illumination.
We propose a method for high-quality facial texture reconstruction from RGB images based on a single smartphone which we equip with an inexpensive polarization foil.
In this work, we propose a 3D compositional morphable model of eyeglasses that accurately incorporates high-fidelity geometric and photometric interaction effects.
We propose using a global point cloud that is dynamically updated each frame, along with a learned fusion approach in image space.
This paper deals with the problem of localizing objects in image and video datasets from visual exemplars.
In this paper, we present AGRoL, a novel conditional diffusion model specially purposed to track full bodies given sparse upper-body tracking signals. Our model uses a simple...