Abstract Three-dimensional (3D) human pose estimation involves estimating the articulated
3D joint locations of a human body from an image or video. Due to its widespread …

Deep neural networks (DNNs) have shown remarkable performance improvements on
vision-related tasks such as object detection or image segmentation. Despite their success …

[CS482] 3D Gaussian Splatting for Real-Time Radiance Field Rendering Page 1 3D Gaussian
Splatting for Real-Time Radiance Field Rendering November 20, 2023 Bernhard Kerbl …

We present GauHuman a 3D human model with Gaussian Splatting for both fast training (1 2
minutes) and real-time rendering (up to 189 FPS) compared with existing NeRF-based …

In this paper we present ADOP, a novel point-based, differentiable neural rendering
pipeline. Like other neural renderers, our system takes as input calibrated camera images …

Rendering bridges the gap between 2D vision and 3D scenes by simulating the physical
process of image formation. By inverting such renderer, one can think of a learning …

Efficient generation of 3D digital humans is important in several industries including virtual
reality social media and cinematic production. 3D generative adversarial networks (GANs) …

Modern rendering systems are confronted with a dauntingly large and growing set of
requirements: in their pursuit of realism, physically based techniques must increasingly …

We present the first real-time method to capture the full global 3D skeletal pose of a human
in a stable, temporally consistent manner using a single RGB camera. Our method combines …

We demonstrate a novel deep neural network capable of reconstructing human full body
pose in real-time from 6 Inertial Measurement Units (IMUs) worn on the user's body. In doing …