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 …

We introduce MVSplat, an efficient model that, given sparse multi-view images as input,
predicts clean feed-forward 3D Gaussians. To accurately localize the Gaussian centers, we …

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

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 …

Image Matching is a core component of all best-performing algorithms and pipelines in 3D
vision. Yet despite matching being fundamentally a 3D problem, intrinsically linked to …

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 …

Abstract 3D human pose estimation has been researched for decades with promising fruits.
3D human pose lifting is one of the promising research directions toward the task where …

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 …