Pose Estimator

Pose estimation, the task of determining the 3D position and orientation of objects or body parts from images or sensor data, aims to achieve accurate and reliable pose predictions across diverse and challenging conditions. Current research emphasizes improving robustness to noise, occlusion, and variations in viewpoint, scale, and background, often employing deep learning models like Vision Transformers and convolutional neural networks, along with techniques such as bundle adjustment and sensor fusion. These advancements are crucial for applications ranging from robotics and autonomous navigation to human-computer interaction and medical imaging, enabling safer and more efficient systems in various fields.