arXiv:2503.01158cs.CV2025-03CVPR被引 2

一键生成游戏角色,支持文本和图像两种输入方式。

EasyCraft: A Robust and Efficient Framework for Automatic Avatar Crafting

  • 采用统一特征编码与参数映射机制,兼容多种游戏引擎。
  • 在两款RPG游戏中实现领先性能,支持跨引擎快速适配。
  • 适合需要个性化角色生成的游戏玩家与开发团队使用。

角色定制(即'面部塑造')是角色扮演游戏(RPG)中的关键功能,通过创建个性化角色提升玩家参与度。现有自动化方法因依赖特定图像域的中间约束,且通常仅支持文本或图像中的一种输入,在不同游戏引擎间泛化能力差。为此,我们提出EasyCraft,一种端到端的前馈框架,首次同时支持文本和图像输入的自动化角色塑造。该方法通过一个翻译器,可将任意风格的人脸图像转换为游戏引擎的塑造参数。我们首先在大规模数据集上通过自监督学习建立翻译器图像编码器的统一特征分布,使任意风格的照片都能嵌入统一特征表示;随后将该统一特征映射至特定游戏引擎的塑造参数,该过程可轻松适配大多数游戏引擎,显著提升泛化性。结合文本到图像技术,EasyCraft亦支持精准的文本驱动角色塑造。实验在两款RPG游戏中验证了方法的有效性,达到当前最优表现,并具备良好跨引擎适应能力。

原文摘要 · Abstract (English)

Character customization, or 'face crafting,' is a vital feature in role-playing games (RPGs), enhancing player engagement by enabling the creation of personalized avatars. Existing automated methods often struggle with generalizability across diverse game engines due to their reliance on the intermediate constraints of specific image domain and typically support only one type of input, either text or image. To overcome these challenges, we introduce EasyCraft, an innovative end-to-end feedforward framework that automates character crafting by uniquely supporting both text and image inputs. Our approach employs a translator capable of converting facial images of any style into crafting parameters. We first establish a unified feature distribution in the translator's image encoder through self-supervised learning on a large-scale dataset, enabling photos of any style to be embedded into a unified feature representation. Subsequently, we map this unified feature distribution to crafting parameters specific to a game engine, a process that can be easily adapted to most game engines and thus enhances EasyCraft's generalizability. By integrating text-to-image techniques with our translator, EasyCraft also facilitates precise, text-based character crafting. EasyCraft's ability to integrate diverse inputs significantly enhances the versatility and accuracy of avatar creation. Extensive experiments on two RPG games demonstrate the effectiveness of our method, achieving state-of-the-art results and facilitating adaptability across various avatar engines.

角色生成多模态输入游戏开发统一特征

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