2 citations · 6 across the 5 of their papers we have counts for
5 papers
DualPrim: Compact 3D Reconstruction with Positive and Negative Primitives
Xiaoxu Meng, Zhongmin Chen, Bo Yang +3
Neural reconstructions often trade structure for fidelity, yielding dense and unstructured meshes with irregular topology and weak part boundaries that hinder editing, animation, a…
SPGen: Spherical Projection as Consistent and Flexible Representation for Single Image 3D Shape Generation
Jingdong Zhang, Weikai Chen, Yuan Liu +6
Existing single-view 3D generative models typically adopt multiview diffusion priors to reconstruct object surfaces, yet they remain prone to inter-view inconsistencies and are una…
NeUDF: Leaning Neural Unsigned Distance Fields with Volume Rendering
Yu-Tao Liu, Li Wang, Jie yang +4
Multi-view shape reconstruction has achieved impressive progresses thanks to the latest advances in neural implicit surface rendering. However, existing methods based on signed dis…
NeAT: Learning Neural Implicit Surfaces with Arbitrary Topologies from Multi-view Images
Xiaoxu Meng, Weikai Chen, Bo Yang
Recent progress in neural implicit functions has set new state-of-the-art in reconstructing high-fidelity 3D shapes from a collection of images. However, these approaches are limit…
3PSDF: Three-Pole Signed Distance Function for Learning Surfaces with Arbitrary Topologies
Weikai Chen, Cheng Lin, Weiyang Li +1
Recent advances in learning 3D shapes using neural implicit functions have achieved impressive results by breaking the previous barrier of resolution and diversity for varying topo…