HybridPlane: A General 4D Representation for Dynamic Scene Reconstruction

Despite recent advances in dynamic scene reconstruction, challenges from imbalanced camera distribution and inaccurate pose estimation in real-world datasets still persist, undermining the spatiotemporal consistency of reconstruction. In this paper, we propose HybridPlane, a novel representation that leverages the complementary advantages of cylindrical and Cartesian coordinate systems to achieve high-quality dynamic scene synthesis. Unlike Cartesian projection, which shares identical features in symmetric regions, cylindrical projection explicitly disentangles features from different viewpoints, thereby improving robustness against imbalanced camera distributions. Moreover, the synergy between these two coordinate systems in both projection and representational capacity enhances the model's ability to capture complex motions and fine-grained details. We further adopt the dynamic positional encoding strategy to enhance the smoothness of temporal interpolation under inaccurate camera poses by progressively regulating high-frequency signals without incurring additional computational overhead. Extensive experiments demonstrate that our versatile representation can be seamlessly integrated into various rendering pipelines, outperforming the previous methods in reconstruction quality while reducing computational and memory costs by approximately one-third.