State-of-the-art video generation models produce remarkable photorealism, but they lack the precise control required to align generated content with specific scene requirements. Furthermore, without an underlying explicit geometry, these models cannot guarantee 3D consistency. Conversely, 3D engines offer granular control over every scene element and provide native 3D consistency by design, yet their output often remains trapped in the "uncanny valley". Bridging this sim-to-real gap requires both structural precision, where the output must exactly preserve the geometry and dynamics of the input, and global semantic transformation, where materials, lighting, and textures must be holistically transformed to achieve photorealism. We present RealMaster, a method that leverages video diffusion models to lift rendered video into photorealistic video while maintaining full alignment with the output of the 3D engine. To train this model, we generate a paired dataset via an anchor-based propagation strategy, where the first and last frames are enhanced for realism and propagated across the intermediate frames using geometric conditioning cues. We then train an IC-LoRA on these paired videos to distill the high-quality outputs of the pipeline into a model that generalizes beyond the pipeline's constraints, handling objects and characters that appear mid-sequence and enabling inference without requiring anchor frames. Evaluated on complex GTA-V sequences, RealMaster significantly outperforms existing video editing baselines, improving photorealism while preserving the geometry, dynamics, and identity specified by the original 3D control.

翻译：当前最先进的视频生成模型能够生成高度逼真的图像，但缺乏对齐生成内容与特定场景需求的精准控制能力。此外，由于缺乏显式底层几何结构，这些模型无法保证三维一致性。反之，三维引擎虽能实现对场景元素的精细控制并天然具备三维一致性，其输出却往往陷入"恐怖谷"效应。弥合仿真与真实之间的鸿沟需要同时满足两个要求：结构精确性（输出必须完整保留输入的几何结构与动态特征）与全局语义转换（材质、光照和纹理需整体变换以实现逼真效果）。本文提出RealMaster方法，利用视频扩散模型将渲染视频提升为逼真视频，同时保持与三维引擎输出的完全对齐。训练该模型时，我们采用基于锚点帧的传播策略构建配对数据集：对首尾帧进行真实感增强，并通过几何条件引导信号将增强效果传播至中间帧。随后，我们在这些配对视频上训练IC-LoRA模块，将管道的高质量输出蒸馏为可超越管道约束的通用模型，使其能处理序列中间出现的新物体与角色，并在推理时无需依赖锚点帧。在复杂GTA-V序列上的评估表明，RealMaster在保留原始三维控制指定的几何结构、动态特征与身份信息的同时，显著提升了逼真度，全面超越了现有视频编辑基线方法。