mlsanityData to 7 Oct 2026

Dite-HRNet: Dynamic Lightweight High-Resolution Network for Human Pose Estimation

arXiv 2204.10762 ↗First posted 22 Apr 2022cs.CVcited by 10

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Abstract (arXiv)

A high-resolution network exhibits remarkable capability in extracting multi-scale features for human pose estimation, but fails to capture long-range interactions between joints and has high computational complexity. To address these problems, we present a Dynamic lightweight High-Resolution Network (Dite-HRNet), which can efficiently extract multi-scale contextual information and model long-range spatial dependency for human pose estimation. Specifically, we propose two methods, dynamic split convolution and adaptive context modeling, and embed them into two novel lightweight blocks, which are named dynamic multi-scale context block and dynamic global context block. These two blocks, as the basic component units of our Dite-HRNet, are specially designed for the high-resolution networks to make full use of the parallel multi-resolution architecture. Experimental results show that the proposed network achieves superior performance on both COCO and MPII human pose estimation datasets, surpassing the state-of-the-art lightweight networks. Code is available at: https://github.com/ZiyiZhang27/Dite-HRNet.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 23 of its 26 references that are in the map. First posted on arXiv 22 Apr 2022.

Builds on

23 of 26 references.

References · 23

  1. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  2. 2018MobileNetV2: Inverted Residuals and Linear Bottleneckscited by 4,773
  3. 2017Squeeze-and-Excitation Networkscited by 4,763
  4. 2017MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applicationscited by 3,827
  5. 2017Non-local Neural Networkscited by 2,290
  6. 2019Searching for MobileNetV3cited by 1,984
  7. 2019Deep High-Resolution Representation Learning for Visual Recognitioncited by 1,417
  8. 2019Deep High-Resolution Representation Learning for Human Pose Estimationcited by 1,339
  9. 2017ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devicescited by 1,194
  10. 2018ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Designcited by 1,132
  11. 2016Stacked Hourglass Networks for Human Pose Estimationcited by 913
  12. 2018Simple Baselines for Human Pose Estimation and Trackingcited by 502
11 more
  1. 2019Dynamic Convolution: Attention over Convolution Kernelscited by 355
  2. 2017Cascaded Pyramid Network for Multi-Person Pose Estimationcited by 341
  3. 2019GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyondcited by 331
  4. 2019CondConv: Conditionally Parameterized Convolutions for Efficient Inferencecited by 273
  5. 2019HigherHRNet: Scale-Aware Representation Learning for Bottom-Up Human Pose Estimationcited by 247
  6. 2019Distribution-Aware Coordinate Representation for Human Pose Estimationcited by 165
  7. 2019MixConv: Mixed Depthwise Convolutional Kernelscited by 108
  8. 2021Lite-HRNet: A Lightweight High-Resolution Networkcited by 91
  9. 2019The Devil is in the Details: Delving into Unbiased Data Processing for Human Pose Estimationcited by 79
  10. 2020Rethinking Bottleneck Structure for Efficient Mobile Network Designcited by 54
  11. 2021PP-LCNet: A Lightweight CPU Convolutional Neural Networkcited by 27

Built on by

Cited by year

Citing papers per year: 2022: 1; 2023: 2; 2024: 4; 2025: 3.

10 papers.

  1. 20222D Human Pose Estimation with Explicit Anatomical Keypoints Structure Constraintscited by 3
  2. 2023Lite-HRNet Plus: Fast and Accurate Facial Landmark Detectioncited by 2
  3. 2024DHRNet: A Dual-Path Hierarchical Relation Network for Multi-Person Pose Estimationcited by 2
  4. 2024MamKPD: A Simple Mamba Baseline for Real-Time 2D Keypoint Detectioncited by 1
  5. 2023BiHRNet: A Binary high-resolution network for Human Pose Estimationcited by 0
  6. 2024Greit-HRNet: Grouped Lightweight High-Resolution Network for Human Pose Estimationcited by 0
  7. 2024Efficient High-Resolution Visual Representation Learning with State Space Model for Human Pose Estimationcited by 0
  8. 2025LGM-Pose: A Lightweight Global Modeling Network for Real-time Human Pose Estimationcited by 0
  9. 2025A Coarse-to-Fine Human Pose Estimation Method based on Two-stage Distillation and Progressive Graph Neural Networkcited by 0
  10. 2025LAPX: Lightweight Hourglass Network with Global Contextcited by 0