Ms. Yuyao Zhang Profile

Yuyao Zhang

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Proceedings Article | 19 July 2024 Paper

DropNet: a drop-based multiview recognition network for 3D model recognition

Zehua Liu, Yuyao Zhang, Tanbao Yan, Lixin Sun

Proceedings Volume 13181, 131810R (2024) https://doi.org/10.1117/12.3031190

KEYWORDS: 3D modeling, Performance modeling, RGB color model, Feature extraction, Data modeling, 3D image processing, Pattern recognition, Overfitting, Education and training, Cameras

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Methods for recognizing 3D models from multiple views have shown remarkable performance in 3D model recognition. The primary challenge faced by these methods is integrating features from multiple views into a single, highly descriptive 3D shape descriptor. This paper proposes a Drop-based Multi-view Recognition Network (DropNet) for accurate recognition of multiple views of 3D models. The proposed DropNet first extracts multi-view features using a backbone network, and then randomly discards individual view features through the DropView module, which makes the number of view combinations that can be learned by the network grow at the level of combinatorial numbers, which can effectively improve the network's ability to recognize multi-views, and at the same time, improve the robustness of the network. Subsequently, the remaining view feature values are randomly discarded by the DropPoint module, which further enhances the robustness of the network and effectively prevents overfitting. The experimental results on benchmark datasets show that the DropNet outperforms several recent approaches in terms of multi-view recognition performance.

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