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Deep learning techniques have made great strides in 3D reconstruction, converting standard RGB images into high-quality 3D models with minimal effort. This review explores the development of these techniques, highlighting key strategies, challenges, and future research directions. In addition, a comparative analysis of different 3D human reconstruction methods has been presented and evaluated on specific datasets including RenderPeople and Bodies Under Flowing Fashion (BUFF) to compare their effectiveness in geometric accuracy and texture quality. Also, the limitations of the Parametric Model-Conditioned Implicit Representation (PaMIR) method have been explored. Improvements have been suggested to improve accuracy in pose estimation and robustness in complex poses, by integrating the advanced HMR 2.0 method. This enhancement highlights the impact of deep learning on converting 2D models into reliable 3D models.

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A Deep Learning Approach for 3D Human Object Reconstruction from 2D Images: Review, Advances, and Limitation

  • 会议论文

  • 发表日期：

    2025年

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  • Omnia A. Al-Eisawi,
  • Esraa A.-R. Hamed,
  • Howida A. Shedeed,
  • Mohamed F. Tolba

摘要

Deep learning techniques have made great strides in 3D reconstruction, converting standard RGB images into high-quality 3D models with minimal effort. This review explores the development of these techniques, highlighting key strategies, challenges, and future research directions. In addition, a comparative analysis of different 3D human reconstruction methods has been presented and evaluated on specific datasets including RenderPeople and Bodies Under Flowing Fashion (BUFF) to compare their effectiveness in geometric accuracy and texture quality. Also, the limitations of the Parametric Model-Conditioned Implicit Representation (PaMIR) method have been explored. Improvements have been suggested to improve accuracy in pose estimation and robustness in complex poses, by integrating the advanced HMR 2.0 method. This enhancement highlights the impact of deep learning on converting 2D models into reliable 3D models.