The recent developments in 3D scene reconstruction and neural rendering have been significantly influenced by advancements in 3D Gaussian Splatting (3DGS) and Neural Radiance Fields (NeRF). These technologies are being pushed to new limits, addressing challenges such as adverse weather conditions, online 3D model generation, and the recovery of 3D scene structures from compressed images. Innovations in these areas are focusing on improving the clarity, detail, and efficiency of 3D reconstructions, as well as enabling real-time rendering capabilities. The integration of multi-view stereo (MVS) techniques and the exploration of Snapshot Compressive Imaging (SCI) for 3D scene recovery are particularly noteworthy, offering new pathways for high-quality 3D modeling and rendering.

Noteworthy Papers

• WeatherGS: Introduces a novel framework for clear 3D scene reconstruction under adverse weather conditions by categorizing and removing weather-related artifacts, significantly outperforming existing methods.
• MVS-GS: Proposes an online multi-view stereo approach for high-quality 3DGS modeling, demonstrating superior performance in challenging outdoor environments compared to state-of-the-art dense SLAM methods.
• Learning Radiance Fields from a Single Snapshot Compressive Image: Explores the use of SCI for 3D scene recovery, integrating NeRF and 3DGS to achieve high-quality reconstructions and real-time rendering capabilities.