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Spectral Gradient Orthogonalization Improves Differentially Private Training at Scale
Sabari Shanmugam, Nick Barnes, Kerry Taylor
Differentially private training adds isotropic Gaussian noise to clipped gradients, corrupting every singular direction equally. In vision models, where spatial correlation concent…
NoiseSDF2NoiseSDF: Learning Clean Neural Fields from Noisy Supervision
Tengkai Wang, Weihao Li, Ruikai Cui +2
Reconstructing accurate implicit surface representations from point clouds remains a challenging task, particularly when data is captured using low-quality scanning devices. These…
NumGrad-Pull: Numerical Gradient Guided Tri-plane Representation for Surface Reconstruction from Point Clouds
Ruikai Cui, Binzhu Xie, Shi Qiu +3
Reconstructing continuous surfaces from unoriented and unordered 3D points is a fundamental challenge in computer vision and graphics. Recent advancements address this problem by t…
LAM3D: Large Image-Point-Cloud Alignment Model for 3D Reconstruction from Single Image
Ruikai Cui, Xibin Song, Weixuan Sun +8
Large Reconstruction Models have made significant strides in the realm of automated 3D content generation from single or multiple input images. Despite their success, these models…