3D Reconstruction of Single-view Sketches Based on Attention Mechanism and Contrastive Loss

The metaverse is a three-dimensional(3D) virtual space that is immersive and interconnected.With the development of technologies such as virtual reality and artificial intelligence,the metaverse is reshaping human lifestyles.3D reconstruction is a core technique for the metaverse,and deep learning-based 3D reconstruction has become a popular research direction in computer vision.To address the problems of inevitable foreground and background ambiguity,drawing style variations,and viewpoint differences in hand-drawn sketches,a single-view sketch 3D reconstruction model based on attention mechanisms and contrastive losses without requiring additional annotations or user interactions is proposed.The model first rectifies the spatial layout of the input sketch using spatial transformers,and then uses the normalized attention module to establish long-distance and multi-level dependencies on the sketch.The global structure information of the sketch is used to alleviate the reconstruction difficulty caused by the ambiguity of the foreground and background.Furthermore,the contrastive loss function is designed to encourage the model to learn view-invariant and style-invariant latent space features of the sketches,so as to improve robustness.Experimental results on multiple datasets demonstrate the effectiveness and advancement of the proposed model.