Search Results for author:
Found 6 papers, 2 papers with code
Learning Neural Transmittance for Efficient Rendering of Reflectance Fields
However, it remains challenging and time-consuming to render such representations under complex lighting such as environment maps, which requires individual ray marching towards each single light to calculate the transmittance at every sampled point.
Real-Time Global Illumination Decomposition of Videos
We propose the first approach for the decomposition of a monocular color video into direct and indirect illumination components in real time.
Inverse Rendering for Complex Indoor Scenes: Shape, Spatially-Varying Lighting and SVBRDF from a Single Image
Our inverse rendering network incorporates physical insights -- including a spatially-varying spherical Gaussian lighting representation, a differentiable rendering layer to model scene appearance, a cascade structure to iteratively refine the predictions and a bilateral solver for refinement -- allowing us to jointly reason about shape, lighting, and reflectance.
VNect: Real-time 3D Human Pose Estimation with a Single RGB Camera
A real-time kinematic skeleton fitting method uses the CNN output to yield temporally stable 3D global pose reconstructions on the basis of a coherent kinematic skeleton.
Ranked #16 on
Pose Estimation
on Leeds Sports Poses
EgoCap: Egocentric Marker-less Motion Capture with Two Fisheye Cameras (Extended Abstract)
Marker-based and marker-less optical skeletal motion-capture methods use an outside-in arrangement of cameras placed around a scene, with viewpoints converging on the center.
EgoCap: Egocentric Marker-less Motion Capture with Two Fisheye Cameras
We therefore propose a new method for real-time, marker-less and egocentric motion capture which estimates the full-body skeleton pose from a lightweight stereo pair of fisheye cameras that are attached to a helmet or virtual reality headset.
