Human pose estimation is a very active research field, stimulated by its important
applications in robotics, entertainment or health and sports sciences, among others …

The understanding of body measurements and body shapes in and between populations is
important and has many applications in medicine, surveying, the fashion industry, fitness …

We introduce pixelSplat a feed-forward model that learns to reconstruct 3D radiance fields
parameterized by 3D Gaussian primitives from pairs of images. Our model features real-time …

Recent transformer-based solutions have been introduced to estimate 3D human pose from
2D keypoint sequence by considering body joints among all frames globally to learn spatio …

Despite significant progress, we show that state of the art 3D human pose and shape
estimation methods remain sensitive to partial occlusion and can produce dramatically …

We present a new method, called MEsh TRansfOrmer (METRO), to reconstruct 3D human
pose and mesh vertices from a single image. Our method uses a transformer encoder to …

Measures of human movement dynamics can predict outcomes like injury risk or
musculoskeletal disease progression. However, these measures are rarely quantified in …

Inferring human-scene contact (HSC) is the first step toward understanding how humans
interact with their surroundings. While detecting 2D human-object interaction (HOI) and …

Human pose estimation deeply relies on visual clues and anatomical constraints between
parts to locate keypoints. Most existing CNN-based methods do well in visual …

While CNN-based models have made remarkable progress on human pose estimation,
what spatial dependencies they capture to localize keypoints remains unclear. In this work …