In real-world scenarios, the diversity of object types and random placement can lead to difficulties in object recognition for intelligent robots, resulting in a low success rate in grasping. A metho
EgoHaFL是一个针对第一人称视角的3D手部预测任务设计的(dataset designed for egocentric (first-person) 3D hand forecasting)数据集,包含视频片段、文本描述、相机内参和基于MANO的详细3D手部标注。支持3D手部预测、手部姿态估计、手部与物体交互理解以及视频-语言建模等研究任务。