Learning-based methods have dominated the 3D human pose estimation (HPE) tasks with
significantly better performance in most benchmarks than traditional optimization-based …

Camera calibration is a crucial component in the realm of sports analytics as it serves as the
foundation to extract 3D information out of the broadcast images. Despite the significance of …

Most existing 3D human pose estimation work rely heavily on the powerful memory
capability of networks to obtain suitable 2D-3D mappings from the training data. Few works …

In recent times, there has been a growing interest in developing effective perception
techniques for combining information from multiple modalities. This involves aligning …

Although 3D human pose estimation has gained impressive development in recent years,
only a few works focus on infants, that have different bone lengths and also have limited …

Multi-object tracking in sports scenarios has become one of the focal points in computer
vision, experiencing significant advancements through the integration of deep learning …

3D human pose estimation (HPE) has become increasingly important in baseball analytic,
but there are several difficulties pertaining to pose estimation in real-world baseball pitching …

Generative modeling of 3D human bodies have been studied extensively in computer vision.
The core is to design a compact latent representation that is both expressive and …

Diffusion models have demonstrated remarkable success in generative modeling. In this
paper, we propose PADS (Pose Analysis by Diffusion Synthesis), a novel framework …

Single camera 3D pose estimation is an ill-defined problem due to inherent ambiguities from
depth, occlusion or keypoint noise. Multi-hypothesis pose estimation accounts for this …