Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: LiDARCap: Long-range Marker-less 3D Human Motion Capture with LiDAR
  Point Clouds   Existing motion capture datasets are largely short-range and cannot yet fit
the need of long-range applications. We propose LiDARHuman26M, a new human
motion capture dataset captured by LiDAR at a much longer range to overcome
this limitation. Our dataset also includes the ground truth human motions
acquired by the IMU system and the synchronous RGB images. We further present a
strong baseline method, LiDARCap, for LiDAR point cloud human motion capture.
Specifically, we first utilize PointNet++ to encode features of points and then
employ the inverse kinematics solver and SMPL optimizer to regress the pose
through aggregating the temporally encoded features hierarchically.
Quantitative and qualitative experiments show that our method outperforms the
techniques based only on RGB images. Ablation experiments demonstrate that our
dataset is challenging and worthy of further research. Finally, the experiments
on the KITTI Dataset and the Waymo Open Dataset show that our method can be
generalized to different LiDAR sensor settings.

25
The categories of this paper are: patt-sol
12
The categories of this paper are: nucl-th
29
The categories of this paper are: funct-an
27
The categories of this paper are: comp-gas
18
The categories of this paper are: econ
3
The categories of this paper are: physics
17
The categories of this paper are: q-fin
10
The categories of this paper are: q-bio
20
The categories of this paper are: acc-phys
11
The categories of this paper are: hep-lat
16
The categories of this paper are: stat
30
The categories of this paper are: q-alg
32
The categories of this paper are: atom-ph
2
The categories of this paper are: math
5
The categories of this paper are: gr-qc
19
The categories of this paper are: eess