Characteristic 3D Pose Dataset

为了训练和评估特征3d姿势预测的任务，我们引入了基于GRAB和human3.6 m的带注释的特征姿势数据集。• Human3.6M是用于人类姿势预测的常用数据集，包括由11个专业参与者在17个场景中执行的210个动作，总共360万帧。通过高速运动捕捉系统获得32个关节的3d位置; 我们在方法中使用了减少的17关节布局，删除了多余和未使用的关节，以下是最近的数据集，在10个不同参与者的1334序列中具有超过100万个帧，它们与各种对象一起执行总共29个动作。每个演员

To train and evaluate the task of feature-based 3D pose prediction, we introduce an annotated feature pose dataset based on GRAB and Human3.6M. • Human3.6M is a widely adopted benchmark dataset for human pose prediction, encompassing 210 actions performed by 11 professional participants across 17 scenarios, with a total of 3.6 million frames. The 3D coordinates of 32 joints are acquired via a high-speed motion capture system; we utilize a simplified 17-joint layout in our approach by removing redundant and unused joints. The following is the recent dataset, which contains more than 1 million frames across 1334 sequences from 10 distinct participants, who execute a total of 29 actions while interacting with various objects. Each actor

搜集汇总

背景与挑战

背景概述

Characteristic 3D Pose Dataset是一个用于特征3D姿势预测任务的数据集，基于Human3.6M和GRAB数据集构建，包含数百万帧的人类动作数据。该数据集由Google和慕尼黑工业大学于2022年发布，适用于训练和评估相关模型。