Splat4D：用于时空一致内容创建的扩散增强4D高斯泼溅
Splat4D: Diffusion-Enhanced 4D Gaussian Splatting for Temporally and Spatially Consistent Content Creation
AI总结：
本文提出Splat4D框架，通过多视角渲染、不一致性识别、视频扩散模型和非对称U-Net细化，从单目视频生成高保真且时空一致的4D内容，在多项基准与应用中达到SOTA。
摘要：
从单目视频生成高质量4D内容（用于数字人和AR/VR等应用）在确保时空一致性、保留复杂细节以及有效结合用户引导方面面临挑战。为克服这些挑战，我们引入了Splat4D，这是一个能从单目视频生成高保真4D内容的新颖框架。Splat4D通过利用多视角渲染、不一致性识别、视频扩散模型和用于细化的非对称U-Net，在保持忠实空间时间相干性的同时实现了卓越性能。通过在公共基准上的广泛评估，Splat4D在各种指标上始终展现出最先进的性能，凸显了我们方法的有效性。此外，Splat4D的多功能性在文本/图像条件4D生成、4D人生成和文本引导内容编辑等各种应用中得到验证，根据用户指令产生连贯的结果。
英文摘要：
Generating high-quality 4D content from monocular videos for applications such as digital humans and AR/VR poses challenges in ensuring temporal and spatial consistency, preserving intricate details, and incorporating user guidance effectively. To overcome these challenges, we introduce Splat4D, a novel framework enabling high-fidelity 4D content generation from a monocular video. Splat4D achieves superior performance while maintaining faithful spatial-temporal coherence by leveraging multi-view rendering, inconsistency identification, a video diffusion model, and an asymmetric U-Net for refinement. Through extensive evaluations on public benchmarks, Splat4D consistently demonstrates state-of-the-art performance across various metrics, underscoring the efficacy of our approach. Additionally, the versatility of Splat4D is validated in various applications such as text/image conditioned 4D generation, 4D human generation, and text-guided content editing, producing coherent outcomes following user instructions.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
