3D reconstruction of toys based on adaptive scaled neural radiation field.

ABSTRACT: With the rapid development of computer vision technology, 3D reconstruction of toys under single-view conditions still faces significant challenges in terms of detail loss and color distortion. For this reason, this article proposes an adaptive scale neural radiance fields (AS-NeRF) model to enhance the accuracy and realism of 3D toy reconstruction. The method constructs a multi-task feature extraction network based on the Vision Transformer, which simultaneously extracts and fuses multidimensional features such as texture, shape, color, and depth through a task dynamic modulation mechanism and a dynamic adapter layer, providing a rich and accurate contextual feature representation. The NeRF model is enhanced to incorporate an adaptive scaling mechanism that dynamically optimizes rendering

SUBMITTER: Zou J 

PROVIDER: S-EPMC12453728 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature