3DProxyImg: Controllable 3D-Aware Animation Synthesis from Single Image via 2D-3D Aligned Proxy Embedding
Yupeng Zhu, Xiongzhen Zhang, Ye Chen, Bingbing Ni

TL;DR
This paper introduces a lightweight framework for 3D animation from a single image that balances high-quality rendering with precise 3D control, using a novel proxy representation to enable efficient, interactive, and coherent animations.
Contribution
It proposes a 2D-3D aligned proxy representation that decouples geometry from appearance, enabling controllable 3D animation without heavy computation or accurate geometry.
Findings
Outperforms video-based methods in identity preservation and consistency.
Enables efficient animation on low-power devices.
Provides high levels of user control and interaction.
Abstract
3D animation is central to modern visual media, yet traditional production pipelines remain labor-intensive, expertise-demanding, and computationally expensive. Recent AIGC-based approaches partially automate asset creation and rigging, but they either inherit the heavy costs of full 3D pipelines or rely on video-synthesis paradigms that sacrifice 3D controllability and interactivity. We focus on single-image 3D animation generation and argue that progress is fundamentally constrained by a trade-off between rendering quality and 3D control. To address this limitation, we propose a lightweight 3D animation framework that decouples geometric control from appearance synthesis. The core idea is a 2D-3D aligned proxy representation that uses a coarse 3D estimate as a structural carrier, while delegating high-fidelity appearance and view synthesis to learned image-space generative priors.…
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Taxonomy
TopicsGenerative Adversarial Networks and Image Synthesis · 3D Shape Modeling and Analysis · Face recognition and analysis
