# 4D Gaussian Splatting with Scale-aware Residual Field and Adaptive Optimization for Real-time Rendering of Temporally Complex Dynamic Scenes

arXiv: https://arxiv.org/abs/2412.06299 · HTML: https://mlsanity.com/paper/2412.06299/

## Key facts

- Cited by 37 papers in the map (data through 14 Oct 2026).
- Builds on 52 of its 76 references that are in the map.
- First posted on arXiv 9 Dec 2024.

## Builds on (most cited first, 30 of 52)

- [3D Gaussian Splatting for Real-Time Radiance Field Rendering](https://mlsanity.com/paper/2308.04079/) (2023)
- [Instant Neural Graphics Primitives with a Multiresolution Hash Encoding](https://mlsanity.com/paper/2201.05989/) (2022)
- [Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields](https://mlsanity.com/paper/2103.13415/) (2021)
- [Plenoxels: Radiance Fields without Neural Networks](https://mlsanity.com/paper/2112.05131/) (2021)
- [D-NeRF: Neural Radiance Fields for Dynamic Scenes](https://mlsanity.com/paper/2011.13961/) (2020)
- [SuperGlue: Learning Feature Matching with Graph Neural Networks](https://mlsanity.com/paper/1911.11763/) (2019)
- [Depth Map Prediction from a Single Image using a Multi-Scale Deep Network](https://mlsanity.com/paper/1406.2283/) (2014)
- [NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collections](https://mlsanity.com/paper/2008.02268/) (2020)
- [4D Gaussian Splatting for Real-Time Dynamic Scene Rendering](https://mlsanity.com/paper/2310.08528/) (2023)
- [Direct Voxel Grid Optimization: Super-fast Convergence for Radiance Fields Reconstruction](https://mlsanity.com/paper/2111.11215/) (2021)
- [PlenOctrees for Real-time Rendering of Neural Radiance Fields](https://mlsanity.com/paper/2103.14024/) (2021)
- [NeRF++: Analyzing and Improving Neural Radiance Fields](https://mlsanity.com/paper/2010.07492/) (2020)
- [MVSNet: Depth Inference for Unstructured Multi-view Stereo](https://mlsanity.com/paper/1804.02505/) (2018)
- [Deformable 3D Gaussians for High-Fidelity Monocular Dynamic Scene Reconstruction](https://mlsanity.com/paper/2309.13101/) (2023)
- [K-Planes: Explicit Radiance Fields in Space, Time, and Appearance](https://mlsanity.com/paper/2301.10241/) (2023)
- [Dynamic 3D Gaussians: Tracking by Persistent Dynamic View Synthesis](https://mlsanity.com/paper/2308.09713/) (2023)
- [Block-NeRF: Scalable Large Scene Neural View Synthesis](https://mlsanity.com/paper/2202.05263/) (2022)
- [KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPs](https://mlsanity.com/paper/2103.13744/) (2021)
- [Neural Body: Implicit Neural Representations with Structured Latent Codes for Novel View Synthesis of Dynamic Humans](https://mlsanity.com/paper/2012.15838/) (2020)
- [RegNeRF: Regularizing Neural Radiance Fields for View Synthesis from Sparse Inputs](https://mlsanity.com/paper/2112.00724/) (2021)
- [HexPlane: A Fast Representation for Dynamic Scenes](https://mlsanity.com/paper/2301.09632/) (2023)
- [HumanNeRF: Free-viewpoint Rendering of Moving People from Monocular Video](https://mlsanity.com/paper/2201.04127/) (2022)
- [Real-time Photorealistic Dynamic Scene Representation and Rendering with 4D Gaussian Splatting](https://mlsanity.com/paper/2310.10642/) (2023)
- [Baking Neural Radiance Fields for Real-Time View Synthesis](https://mlsanity.com/paper/2103.14645/) (2021)
- [Modular Primitives for High-Performance Differentiable Rendering](https://mlsanity.com/paper/2011.03277/) (2020)
- [SC-GS: Sparse-Controlled Gaussian Splatting for Editable Dynamic Scenes](https://mlsanity.com/paper/2312.14937/) (2023)
- [Fast Dynamic Radiance Fields with Time-Aware Neural Voxels](https://mlsanity.com/paper/2205.15285/) (2022)
- [Spacetime Gaussian Feature Splatting for Real-Time Dynamic View Synthesis](https://mlsanity.com/paper/2312.16812/) (2023)
- [FSGS: Real-Time Few-shot View Synthesis using Gaussian Splatting](https://mlsanity.com/paper/2312.00451/) (2023)
- [DNGaussian: Optimizing Sparse-View 3D Gaussian Radiance Fields with Global-Local Depth Normalization](https://mlsanity.com/paper/2403.06912/) (2024)

## Built on by (most cited first, 30 of 37)

- [Swift4D:Adaptive divide-and-conquer Gaussian Splatting for compact and efficient reconstruction of dynamic scene](https://mlsanity.com/paper/2503.12307/) (2025)
- [Instant Gaussian Stream: Fast and Generalizable Streaming of Dynamic Scene Reconstruction via Gaussian Splatting](https://mlsanity.com/paper/2503.16979/) (2025)
- [4DGC: Rate-Aware 4D Gaussian Compression for Efficient Streamable Free-Viewpoint Video](https://mlsanity.com/paper/2503.18421/) (2025)
- [ReCon-GS: Continuum-Preserved Gaussian Streaming for Fast and Compact Reconstruction of Dynamic Scenes](https://mlsanity.com/paper/2509.24325/) (2025)
- [4DGCPro: Efficient Hierarchical 4D Gaussian Compression for Progressive Volumetric Video Streaming](https://mlsanity.com/paper/2509.17513/) (2025)
- [Light4GS: Lightweight Compact 4D Gaussian Splatting Generation via Context Model](https://mlsanity.com/paper/2503.13948/) (2025)
- [DyTact: Capturing Dynamic Contacts in Hand-Object Manipulation](https://mlsanity.com/paper/2506.03103/) (2025)
- [DASH: 4D Hash Encoding with Self-Supervised Decomposition for Real-Time Dynamic Scene Rendering](https://mlsanity.com/paper/2507.19141/) (2025)
- [ADC-GS: Anchor-Driven Deformable and Compressed Gaussian Splatting for Dynamic Scene Reconstruction](https://mlsanity.com/paper/2505.08196/) (2025)
- [E-4DGS: High-Fidelity Dynamic Reconstruction from the Multi-view Event Cameras](https://mlsanity.com/paper/2508.09912/) (2025)
- [Prior-Enhanced Gaussian Splatting for Dynamic Scene Reconstruction from Casual Video](https://mlsanity.com/paper/2512.11356/) (2025)
- [Motion Matters: Compact Gaussian Streaming for Free-Viewpoint Video Reconstruction](https://mlsanity.com/paper/2505.16533/) (2025)
- [Scale-GS: Efficient Scalable Gaussian Splatting via Redundancy-filtering Training on Streaming Content](https://mlsanity.com/paper/2508.21444/) (2025)
- [Color3D: Controllable and Consistent 3D Colorization with Personalized Colorizer](https://mlsanity.com/paper/2510.10152/) (2025)
- [MoE-GS: Mixture of Experts for Dynamic Gaussian Splatting](https://mlsanity.com/paper/2510.19210/) (2025)
- [StreamSTGS: Streaming Spatial and Temporal Gaussian Grids for Real-Time Free-Viewpoint Video](https://mlsanity.com/paper/2511.06046/) (2025)
- [PackUV: Packed Gaussian UV Maps for 4D Volumetric Video](https://mlsanity.com/paper/2602.23040/) (2026)
- [MoRGS: Efficient Per-Gaussian Motion Reasoning for Streamable Dynamic 3D Scenes](https://mlsanity.com/paper/2603.25042/) (2026)
- [Online Segment 3D Gaussians via Launching Virtual Drones](https://mlsanity.com/paper/2607.01628/) (2026)
- [On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting](https://mlsanity.com/paper/2607.08250/) (2026)
- [Reconstructing the Dynamic World: A Representation-Centric View of 4D Scene Reconstruction](https://mlsanity.com/paper/2609.39960/) (2026)
- [LoGoColor: Local-Global 3D Colorization for 360deg Scenes](https://mlsanity.com/paper/2512.09278/) (2025)
- [HGS: Hybrid Gaussian Splatting with Static-Dynamic Decomposition for Compact Dynamic View Synthesis](https://mlsanity.com/paper/2512.14352/) (2025)
- [SplatBus: A Gaussian Splatting Viewer Framework via GPU Interprocess Communication](https://mlsanity.com/paper/2601.15431/) (2026)
- [Constrained Dynamic Gaussian Splatting](https://mlsanity.com/paper/2602.03538/) (2026)
- [CAGS: Color-Adaptive Volumetric Video Streaming with Dynamic 3D Gaussian Splatting](https://mlsanity.com/paper/2605.09279/) (2026)
- [PaMoSplat: Part-Aware Motion-Guided Gaussian Splatting for Dynamic Scene Reconstruction](https://mlsanity.com/paper/2605.10307/) (2026)
- [Temporally Aware Densification for Dynamic 3D Gaussian Splatting](https://mlsanity.com/paper/2606.23212/) (2026)
- [DLGStream: Dynamic Language-embedded Guassian Splatting for Open-vocabulary Enabled Free-viewpoint Video Streaming](https://mlsanity.com/paper/2606.28840/) (2026)
- [ACA-GS: Adaptive-Capacity Anchored Gaussian Splatting for Compact Dynamic Radiance Fields](https://mlsanity.com/paper/2608.04581/) (2026)

## Abstract (arXiv)

Reconstructing dynamic scenes from video sequences is a highly promising task in the multimedia domain. While previous methods have made progress, they often struggle with slow rendering and managing temporal complexities such as significant motion and object appearance/disappearance. In this paper, we propose SaRO-GS as a novel dynamic scene representation capable of achieving real-time rendering while effectively handling temporal complexities in dynamic scenes. To address the issue of slow rendering speed, we adopt a Gaussian primitive-based representation and optimize the Gaussians in 4D space, which facilitates real-time rendering with the assistance of 3D Gaussian Splatting. Additionally, to handle temporally complex dynamic scenes, we introduce a Scale-aware Residual Field. This field considers the size information of each Gaussian primitive while encoding its residual feature and aligns with the self-splitting behavior of Gaussian primitives. Furthermore, we propose an Adaptive Optimization Schedule, which assigns different optimization strategies to Gaussian primitives based on their distinct temporal properties, thereby expediting the reconstruction of dynamic regions. Through evaluations on monocular and multi-view datasets, our method has demonstrated state-of-the-art performance. Please see our project page at https://yjb6.github.io/SaRO-GS.github.io.