MeTRAbs: Metric-Scale Truncation-Robust Heatmaps for Absolute 3D Human Pose Estimation

István Sárándi, Timm Linder, Kai Oliver Arras, Bastian Leibe
IEEE Transactions on Biometrics, Behavior, and Identity Science (T-BIOM), Selected Best Works From Automatic Face and Gesture Recognition 2020 (to appear)

Heatmap representations have formed the basis of human pose estimation systems for many years, and their extension to 3D has been a fruitful line of recent research. This includes 2.5D volumetric heatmaps, whose X and Y axes correspond to image space and Z to metric depth around the subject. To obtain metric-scale predictions, 2.5D methods need a separate post-processing step to resolve scale ambiguity. Further, they cannot localize body joints outside the image boundaries, leading to incomplete estimates for truncated images. To address these limitations, we propose metric-scale truncation-robust (MeTRo) volumetric heatmaps, whose dimensions are all defined in metric 3D space, instead of being aligned with image space. This reinterpretation of heatmap dimensions allows us to directly estimate complete, metric-scale poses without test-time knowledge of distance or relying on anthropometric heuristics, such as bone lengths. To further demonstrate the utility our representation, we present a differentiable combination of our 3D metric-scale heatmaps with 2D image-space ones to estimate absolute 3D pose (our MeTRAbs architecture). We find that supervision via absolute pose loss is crucial for accurate non-root-relative localization. Using a ResNet-50 backbone without further learned layers, we obtain state-of-the-art results on Human3.6M, MPI-INF-3DHP and MuPoTS-3D. Our code is publicly available to facilitate further research.

Winning submission at the ECCV 2020 3D Poses in the Wild Challenge
» Show BibTeX

title={MeTRAbs: Metric-Scale Truncation-Robust Heatmaps for Absoute 3{D} Human Pose Estimation},
author={Istv\'an S\'ar\'andi and Timm Linder and Kai O. Arras and Bastian Leibe},
journal={IEEE Transactions on Biometrics, Behavior, and Identity Science},
note={in press}

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