Congratualtions!

Our paper has been accepted to the IEEE International Conference on Image Processing (ICIP) 2025 [LINK]

  • Title: Enhancing 3D Scene Representation with Structural Dissimilarity-Aware Learning

  • Authors: Seungjae Lee, Ho Jun Kim, and Hak Gu Kim

  • Abstract: Novel view synthesis aims to generate high-quality unseen views from images at different viewpoints. However, the existing methods often struggle to preserve fine details, leading to structural distortions in complex regions. In this paper, we introduce a simple yet effective structure-aware objective function designed to enhance structural information in novel view synthesis. By leveraging the Structural Similarity Index (SSIM), our method attends to regions exhibiting significant structural distortions. We incorporate structural dissimilarity-based attention to highlight discrepancies in challenging regions between predicted and ground-truth images. It enables recent 3D scene representation models to achieve improved structure preservation, leading to more coherent representations. Experiments on synthetic and real-world datasets demonstrate that our approach enhances structural consistency, particularly in challenging regions, making it a valuable addition to state-of-the-arts.