Digs: Divergence guided shape implicit neural representation for unoriented point clouds

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Towards better gradient consistency for neural signed distance functions via level set alignment

B Ma, J Zhou, YS Liu, Z Han - Proceedings of the IEEE/CVF …, 2023 - openaccess.thecvf.com
Neural signed distance functions (SDFs) have shown remarkable capability in representing
geometry with details. However, without signed distance supervision, it is still a challenge to …
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Advances in 3d generation: A survey

X Li, Q Zhang, D Kang, W Cheng, Y Gao… - ar**
J Zhou, B Ma, YS Liu - IEEE transactions on pattern analysis …, 2024 - ieeexplore.ieee.org
Learning signed distance functions (SDFs) from point clouds is an important task in 3D
computer vision. However, without ground truth signed distances, point normals or clean …
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