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CVPR2025顶会

SfM-Free 3D Gaussian Splatting via Hierarchical Training

Bo Ji, Angela Yao

2025年份
9顶会引用

摘要

Figure 1 . Novel view synthesis results (left) alongside the projected centers of 3D Gaussians (right). Each blue dot represents a projected 3D Gaussian center. Our proposal offers two key advantages: 1) Our 3D Gaussians are well-distributed across the scene, whereas CF-3DGS [11] has a notable absence of 3D Gaussians on the image's left side (e.g., in the red region); 2) Our learned 3D Gaussians are of high quality. While CF-3DGS places numerous 3D Gaussians in the green region, the rendering quality there is notably inferior to ours.

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