论文标题
一项有关深生成3D感知图像合成的调查
A Survey on Deep Generative 3D-aware Image Synthesis
论文作者
论文摘要
近年来，深度学习有能力的视觉内容创建的进展显着。其中包括深层生成的3D感知图像合成，该图像以3D一致的方式产生了高思维图像，同时从纯图像集合中捕获了物体的紧凑表面，而无需任何3D监督，从而弥合了2D图像和3D现实之间的间隙。最近，在过去几年（主要是过去两年）中，有数百篇论文出现在顶级期刊和会议中，但在顶级期刊和会议中出现了数百篇论文，但缺乏对这一出色和迅速进步的全面调查。我们的调查旨在向新的研究人员介绍该主题，为相关工作提供有用的参考，并通过我们的讨论部分刺激未来的研究方向。除了介绍的论文外，我们的目标是不断更新最新的相关论文，并在https://weihaox.github.io/3d-aware-gen上进行相应的实现。
Recent years have seen remarkable progress in deep learning powered visual content creation. This includes deep generative 3D-aware image synthesis, which produces high-idelity images in a 3D-consistent manner while simultaneously capturing compact surfaces of objects from pure image collections without the need for any 3D supervision, thus bridging the gap between 2D imagery and 3D reality. The ield of computer vision has been recently captivated by the task of deep generative 3D-aware image synthesis, with hundreds of papers appearing in top-tier journals and conferences over the past few years (mainly the past two years), but there lacks a comprehensive survey of this remarkable and swift progress. Our survey aims to introduce new researchers to this topic, provide a useful reference for related works, and stimulate future research directions through our discussion section. Apart from the presented papers, we aim to constantly update the latest relevant papers along with corresponding implementations at https://weihaox.github.io/3D-aware-Gen.
