KAMA: 3D Keypoint Aware Body Mesh Articulation

27 Apr 2021  ·  Umar Iqbal, Kevin Xie, Yunrong Guo, Jan Kautz, Pavlo Molchanov ·

We present KAMA, a 3D Keypoint Aware Mesh Articulation approach that allows us to estimate a human body mesh from the positions of 3D body keypoints. To this end, we learn to estimate 3D positions of 26 body keypoints and propose an analytical solution to articulate a parametric body model, SMPL, via a set of straightforward geometric transformations. Since keypoint estimation directly relies on image clues, our approach offers significantly better alignment to image content when compared to state-of-the-art approaches. Our proposed approach does not require any paired mesh annotations and is able to achieve state-of-the-art mesh fittings through 3D keypoint regression only. Results on the challenging 3DPW and Human3.6M demonstrate that our approach yields state-of-the-art body mesh fittings.

PDF Abstract

Results from the Paper


Task Dataset Model Metric Name Metric Value Global Rank Benchmark
3D Human Pose Estimation 3DPW KAMA PA-MPJPE 51.1 # 57
MPVPE 97.0 # 47
3D Human Pose Estimation Human3.6M KAMA PA-MPJPE 40.2 # 55

Methods