# VoxelKeypointFusion: Generalizable Multi-View Multi-Person Pose Estimation

arXiv: https://arxiv.org/abs/2410.18723 · HTML: https://mlsanity.com/paper/2410.18723/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 23 of its 33 references that are in the map.
- First posted on arXiv 24 Oct 2024.

## Builds on (most cited first, 23 of 23)

- [RTMPose: Real-Time Multi-Person Pose Estimation based on MMPose](https://mlsanity.com/paper/2303.07399/) (2023)
- [Learnable Triangulation of Human Pose](https://mlsanity.com/paper/1905.05754/) (2019)
- [V2V-PoseNet: Voxel-to-Voxel Prediction Network for Accurate 3D Hand and Human Pose Estimation from a Single Depth Map](https://mlsanity.com/paper/1711.07399/) (2017)
- [Fast and Robust Multi-Person 3D Pose Estimation from Multiple Views](https://mlsanity.com/paper/1901.04111/) (2019)
- [MVOR: A Multi-view RGB-D Operating Room Dataset for 2D and 3D Human Pose Estimation](https://mlsanity.com/paper/1808.08180/) (2018)
- [4D Association Graph for Realtime Multi-person Motion Capture Using Multiple Video Cameras](https://mlsanity.com/paper/2002.12625/) (2020)
- [AdaFuse: Adaptive Multiview Fusion for Accurate Human Pose Estimation in the Wild](https://mlsanity.com/paper/2010.13302/) (2020)
- [Faster VoxelPose: Real-time 3D Human Pose Estimation by Orthographic Projection](https://mlsanity.com/paper/2207.10955/) (2022)
- [Multi-View Multi-Person 3D Pose Estimation with Plane Sweep Stereo](https://mlsanity.com/paper/2104.02273/) (2021)
- [Graph-Based 3D Multi-Person Pose Estimation Using Multi-View Images](https://mlsanity.com/paper/2109.05885/) (2021)
- [Pose for Everything: Towards Category-Agnostic Pose Estimation](https://mlsanity.com/paper/2207.10387/) (2022)
- [A generalizable approach for multi-view 3D human pose regression](https://mlsanity.com/paper/1804.10462/) (2018)
- [Generalizable Human Pose Triangulation](https://mlsanity.com/paper/2110.00280/) (2021)
- [H3WB: Human3.6M 3D WholeBody Dataset and Benchmark](https://mlsanity.com/paper/2211.15692/) (2022)
- [TEMPO: Efficient Multi-View Pose Estimation, Tracking, and Forecasting](https://mlsanity.com/paper/2309.07910/) (2023)
- [SelfPose3d: Self-Supervised Multi-Person Multi-View 3d Pose Estimation](https://mlsanity.com/paper/2404.02041/) (2024)
- [A Multi-view RGB-D Approach for Human Pose Estimation in Operating Rooms](https://mlsanity.com/paper/1701.07372/) (2017)
- [Learnable human mesh triangulation for 3D human pose and shape estimation](https://mlsanity.com/paper/2208.11251/) (2022)
- [Part-Aware Measurement for Robust Multi-View Multi-Human 3D Pose Estimation and Tracking](https://mlsanity.com/paper/2106.11589/) (2021)
- [Iterative Greedy Matching for 3D Human Pose Tracking from Multiple Views](https://mlsanity.com/paper/2101.09745/) (2021)
- [Scribosermo: Fast Speech-to-Text models for German and other Languages](https://mlsanity.com/paper/2110.07982/) (2021)
- [Reconstructing Close Human Interactions from Multiple Views](https://mlsanity.com/paper/2401.16173/) (2024)
- [Real-time marker-less multi-person 3D pose estimation in RGB-Depth camera networks](https://mlsanity.com/paper/1710.06235/) (2017)

## Built on by (most cited first, 3 of 3)

- [RapidPoseTriangulation: Multi-view Multi-person Whole-body Human Pose Triangulation in a Millisecond](https://mlsanity.com/paper/2503.21692/) (2025)
- [SimpleDepthPose: Fast and Reliable Human Pose Estimation with RGBD-Images](https://mlsanity.com/paper/2501.18478/) (2025)
- [Skarimva: Skeleton-based Action Recognition is a Multi-view Application](https://mlsanity.com/paper/2602.23231/) (2026)

## Abstract (arXiv)

In the rapidly evolving field of computer vision, the task of accurately estimating the poses of multiple individuals from various viewpoints presents a formidable challenge, especially if the estimations should be reliable as well. This work presents an extensive evaluation of the generalization capabilities of multi-view multi-person pose estimators to unseen datasets and presents a new algorithm with strong performance in this task. It also studies the improvements by additionally using depth information. Since the new approach can not only generalize well to unseen datasets, but also to different keypoints, the first multi-view multi-person whole-body estimator is presented. To support further research on those topics, all of the work is publicly accessible.