Learning Density Regulated and Multi-View Consistent Unsigned Distance Fields. Abstract: Learning unsigned distance fields (UDF) directly from raw point clouds as the implicit representation for surface reconstruction is a promising learning-based method for reconstructing open surfaces and supervision-free attributes.
ABSTRACT. Learning unsigned distance fields (UDF) directly from raw point clouds as the implicit representation for surface recon- struction is a promising ...
The proposed DM-UDF is a method that learns density-regulated and multi-view consistent UDFs by revising CD loss with the dynamic three-phase loss function, ...
Download Citation | On Apr 14, 2024, Rui Zhang and others published Learning Density Regulated and Multi-View Consistent Unsigned Distance Fields | Find, ...
Specifically, we design an Up-UNet feature expansion module which is capable of learning the local and global point features via a down-feature operator and an ...
Apr 18, 2024 · Learning Density Regulated and Multi-view Consistent Unsigned Distance Fields ; Session: MMSP-L5: Multimodal Processing: Vision + Language 2 ...
Learning Density Regulated and Multi-View Consistent Unsigned Distance Fields. R. Zhang, J. Xu, W. Yang, L. Ma, M. Chen, and B. Fei. ICASSP, page 8366-8370.
Article "Learning Density Regulated and Multi-View Consistent Unsigned Distance Fields" Detailed information of the J-GLOBAL is an information service ...
We train NeuralUDF by enforcing the consistency of the rendered colors and the ground truth colors of the input im- ages without using 3D ground truth ...
A novel method to learn consistency-aware unsigned distance functions directly from raw point clouds is proposed by learning to move 3D queries to reach the ...