S²VAE replaces Gaussian bottlenecks with hyperspherical Power Spherical latents in a VAE on VGGT features, yielding better results on depth estimation, camera pose recovery, and point cloud reconstruction especially at high compression.
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Beyond Gaussian Bottlenecks: Topologically Aligned Encoding of Vision-Transformer Feature Spaces
S²VAE replaces Gaussian bottlenecks with hyperspherical Power Spherical latents in a VAE on VGGT features, yielding better results on depth estimation, camera pose recovery, and point cloud reconstruction especially at high compression.