Abstract:

Few-shot 3D reconstruction is considered one of the classic applications of the third generation of artificial intelligence.In the area of computer graphics and computer vision, few-shot 3D reconstruction has attracted the attention of many researchers during the past several decades because of its wide application scenarios and high research value.The area has grown significantly in recent years after the introduction of deep learning methods.The state-of-the-art methods in image-based few-shot 3D reconstruction were reviewed comprehensively and the series of works of our research group were introduced.The various 3D data types were introduced, and their applicability and general processing procedures in 3D reconstruction were discussed.Furthermore, the most widely used datasets were categorized.Finally, some representative experimental results of common 3D reconstructions were presented, and potential future research directions were proposed.

Key words: 3D reconstruction, few-shot learning, human reconstruction