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20222025
most citedImplicit Neural Surface Deformation with Explicit Velocity Fields

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20251 cited

Implicit Neural Surface Deformation with Explicit Velocity Fields

Lu Sang, Zehranaz Canfes, Dongliang Cao +2

In this work, we introduce the first unsupervised method that simultaneously predicts time-varying neural implicit surfaces and deformations between pairs of point clouds. We propo…

cs.CV2024

Synchronous Diffusion for Unsupervised Smooth Non-Rigid 3D Shape Matching

Dongliang Cao, Zorah Laehner, Florian Bernard

Most recent unsupervised non-rigid 3D shape matching methods are based on the functional map framework due to its efficiency and superior performance. Nevertheless, respective meth…

cs.CV2024

Spectral Meets Spatial: Harmonising 3D Shape Matching and Interpolation

Dongliang Cao, Marvin Eisenberger, Nafie El Amrani +2

Although 3D shape matching and interpolation are highly interrelated, they are often studied separately and applied sequentially to relate different 3D shapes, thus resulting in su…

eess.IV2023

DefCor-Net: Physics-Aware Ultrasound Deformation Correction

Zhongliang Jiang, Yue Zhou, Dongliang Cao +1

The recovery of morphologically accurate anatomical images from deformed ones is challenging in ultrasound (US) image acquisition, but crucial to accurate and consistent diagnosis,…

cs.CV2022

Unsupervised Deep Multi-Shape Matching

Dongliang Cao, Florian Bernard

3D shape matching is a long-standing problem in computer vision and computer graphics. While deep neural networks were shown to lead to state-of-the-art results in shape matching,…