# MultiPoseNet: Fast Multi-Person Pose Estimation using Pose Residual Network

arXiv: https://arxiv.org/abs/1807.04067 · HTML: https://mlsanity.com/paper/1807.04067/

## Key facts

- Cited by 47 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Jul 2018.

## Built on by (most cited first, 30 of 47)

- [Bottom-Up Human Pose Estimation Via Disentangled Keypoint Regression](https://mlsanity.com/paper/2104.02300/) (2021)
- [SimCC: a Simple Coordinate Classification Perspective for Human Pose Estimation](https://mlsanity.com/paper/2107.03332/) (2021)
- [Encoder-decoder with Multi-level Attention for 3D Human Shape and Pose Estimation](https://mlsanity.com/paper/2109.02303/) (2021)
- [OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association](https://mlsanity.com/paper/2103.02440/) (2021)
- [Online Knowledge Distillation for Efficient Pose Estimation](https://mlsanity.com/paper/2108.02092/) (2021)
- [Deep Dual Consecutive Network for Human Pose Estimation](https://mlsanity.com/paper/2103.07254/) (2021)
- [Recent Advances in Monocular 2D and 3D Human Pose Estimation: A Deep Learning Perspective](https://mlsanity.com/paper/2104.11536/) (2021)
- [Human Pose as Compositional Tokens](https://mlsanity.com/paper/2303.11638/) (2023)
- [FCPose: Fully Convolutional Multi-Person Pose Estimation with Dynamic Instance-Aware Convolutions](https://mlsanity.com/paper/2105.14185/) (2021)
- [Multi-Instance Pose Networks: Rethinking Top-Down Pose Estimation](https://mlsanity.com/paper/2101.11223/) (2021)
- [Temporal Feature Alignment and Mutual Information Maximization for Video-Based Human Pose Estimation](https://mlsanity.com/paper/2203.15227/) (2022)
- [PandaNet : Anchor-Based Single-Shot Multi-Person 3D Pose Estimation](https://mlsanity.com/paper/2101.02471/) (2021)
- [2D Human Pose Estimation: A Survey](https://mlsanity.com/paper/2204.07370/) (2022)
- [Vision-Based Human Pose Estimation via Deep Learning: A Survey](https://mlsanity.com/paper/2308.13872/) (2023)
- [The Center of Attention: Center-Keypoint Grouping via Attention for Multi-Person Pose Estimation](https://mlsanity.com/paper/2110.05132/) (2021)
- [Reconstructing Groups of People with Hypergraph Relational Reasoning](https://mlsanity.com/paper/2308.15844/) (2023)
- [Mutual Information-Based Temporal Difference Learning for Human Pose Estimation in Video](https://mlsanity.com/paper/2303.08475/) (2023)
- [Person Re-identification: A Retrospective on Domain Specific Open Challenges and Future Trends](https://mlsanity.com/paper/2202.13121/) (2022)
- [DeepSportLab: a Unified Framework for Ball Detection, Player Instance Segmentation and Pose Estimation in Team Sports Scenes](https://mlsanity.com/paper/2112.00627/) (2021)
- [Improving Few-Shot Part Segmentation using Coarse Supervision](https://mlsanity.com/paper/2204.05393/) (2022)
- [Iterative Greedy Matching for 3D Human Pose Tracking from Multiple Views](https://mlsanity.com/paper/2101.09745/) (2021)
- [Dynamic Graph Reasoning for Multi-person 3D Pose Estimation](https://mlsanity.com/paper/2207.11341/) (2022)
- [Keypoint Communities](https://mlsanity.com/paper/2110.00988/) (2021)
- [Domain-Adaptive 2D Human Pose Estimation via Dual Teachers in Extremely Low-Light Conditions](https://mlsanity.com/paper/2407.15451/) (2024)
- [Human Pose-based Estimation, Tracking and Action Recognition with Deep Learning: A Survey](https://mlsanity.com/paper/2310.13039/) (2023)
- [SIMPLE: SIngle-network with Mimicking and Point Learning for Bottom-up Human Pose Estimation](https://mlsanity.com/paper/2104.02486/) (2021)
- [HR-Crime: Human-Related Anomaly Detection in Surveillance Videos](https://mlsanity.com/paper/2108.00246/) (2021)
- [Bottom-Up 2D Pose Estimation via Dual Anatomical Centers for Small-Scale Persons](https://mlsanity.com/paper/2208.11975/) (2022)
- [Test-time Adaptation vs. Training-time Generalization: A Case Study in Human Instance Segmentation using Keypoints Estimation](https://mlsanity.com/paper/2212.06242/) (2022)
- [Multitask Network for Joint Object Detection, Semantic Segmentation and Human Pose Estimation in Vehicle Occupancy Monitoring](https://mlsanity.com/paper/2205.01515/) (2022)

## Abstract (arXiv)

In this paper, we present MultiPoseNet, a novel bottom-up multi-person pose estimation architecture that combines a multi-task model with a novel assignment method. MultiPoseNet can jointly handle person detection, keypoint detection, person segmentation and pose estimation problems. The novel assignment method is implemented by the Pose Residual Network (PRN) which receives keypoint and person detections, and produces accurate poses by assigning keypoints to person instances. On the COCO keypoints dataset, our pose estimation method outperforms all previous bottom-up methods both in accuracy (+4-point mAP over previous best result) and speed; it also performs on par with the best top-down methods while being at least 4x faster. Our method is the fastest real time system with 23 frames/sec. Source code is available at: https://github.com/mkocabas/pose-residual-network