RadSplat：基於輝度場資訊的高斯飛濺，實現穩健的實時渲染，達到每秒900幀。

摘要

近期在視角合成和實時渲染方面取得了顯著的進展，以令人印象深刻的渲染速度實現了逼真的質量。儘管基於輻射場的方法在具有挑戰性的場景（如野外捕捉和大規模場景）中實現了最先進的質量，但它們通常受到與體積渲染相關的過高計算需求的困擾。另一方面，基於高斯飛濺的方法依賴光柵化，自然實現實時渲染，但在更具挑戰性的場景中表現不佳，因為其脆弱的優化啟發法。在這項工作中，我們提出了RadSplat，一種輕量級方法，用於強大的實時渲染複雜場景。我們的主要貢獻有三個。首先，我們使用輻射場作為優化基於點的場景表示的先驗和監督信號，從而提高質量並實現更強大的優化。接下來，我們開發了一種新的修剪技術，減少整體點數，同時保持高質量，從而產生更小、更緊湊的場景表示，並實現更快的推理速度。最後，我們提出了一種新的測試時間過濾方法，進一步加速渲染，並實現對更大、房屋大小場景的擴展。我們發現我們的方法實現了在900+ FPS時的複雜捕捉的最先進合成。

English

Recent advances in view synthesis and real-time rendering have achieved photorealistic quality at impressive rendering speeds. While Radiance Field-based methods achieve state-of-the-art quality in challenging scenarios such as in-the-wild captures and large-scale scenes, they often suffer from excessively high compute requirements linked to volumetric rendering. Gaussian Splatting-based methods, on the other hand, rely on rasterization and naturally achieve real-time rendering but suffer from brittle optimization heuristics that underperform on more challenging scenes. In this work, we present RadSplat, a lightweight method for robust real-time rendering of complex scenes. Our main contributions are threefold. First, we use radiance fields as a prior and supervision signal for optimizing point-based scene representations, leading to improved quality and more robust optimization. Next, we develop a novel pruning technique reducing the overall point count while maintaining high quality, leading to smaller and more compact scene representations with faster inference speeds. Finally, we propose a novel test-time filtering approach that further accelerates rendering and allows to scale to larger, house-sized scenes. We find that our method enables state-of-the-art synthesis of complex captures at 900+ FPS.

RadSplat：基於輝度場資訊的高斯飛濺，實現穩健的實時渲染，達到每秒900幀。

RadSplat: Radiance Field-Informed Gaussian Splatting for Robust Real-Time Rendering with 900+ FPS

摘要

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