74 citations · 634 across the 41 of their papers we have counts for
9 papers · 1 filter
Continuous Curve Textures
Peihan Tu, Li-Yi Wei, Koji Yatani +2
Repetitive patterns are ubiquitous in natural and human-made objects, and can be created with a variety of tools and methods. Manual authoring provides unmatched degree of freedom…
Neural-Pull: Learning Signed Distance Functions from Point Clouds by Learning to Pull Space onto Surfaces
Baorui Ma, Zhizhong Han, Yu-Shen Liu +1
Reconstructing continuous surfaces from 3D point clouds is a fundamental operation in 3D geometry processing. Several recent state-of-the-art methods address this problem using neu…
Improved Modeling of 3D Shapes with Multi-view Depth Maps
Kamal Gupta, Susmija Jabbireddy, Ketul Shah +2
We present a simple yet effective general-purpose framework for modeling 3D shapes by leveraging recent advances in 2D image generation using CNNs. Using just a single depth image…
DRWR: A Differentiable Renderer without Rendering for Unsupervised 3D Structure Learning from Silhouette Images
Zhizhong Han, Chao Chen, Yu-Shen Liu +1
Differentiable renderers have been used successfully for unsupervised 3D structure learning from 2D images because they can bridge the gap between 3D and 2D. To optimize 3D shape p…
Fine-Grained 3D Shape Classification with Hierarchical Part-View Attentions
Xinhai Liu, Zhizhong Han, Yu-Shen Liu +1
Fine-grained 3D shape classification is important for shape understanding and analysis, which poses a challenging research problem. However, the studies on the fine-grained 3D shap…
LRC-Net: Learning Discriminative Features on Point Clouds by Encoding Local Region Contexts
Xinhai Liu, Zhizhong Han, Fangzhou Hong +2
Learning discriminative feature directly on point clouds is still challenging in the understanding of 3D shapes. Recent methods usually partition point clouds into local region set…
SeqXY2SeqZ: Structure Learning for 3D Shapes by Sequentially Predicting 1D Occupancy Segments From 2D Coordinates
Zhizhong Han, Guanhui Qiao, Yu-Shen Liu +1
Structure learning for 3D shapes is vital for 3D computer vision. State-of-the-art methods show promising results by representing shapes using implicit functions in 3D that are lea…
ORCSolver: An Efficient Solver for Adaptive GUI Layout with OR-Constraints
Yue Jiang, Wolfgang Stuerzlinger, Matthias Zwicker +1
OR-constrained (ORC) graphical user interface layouts unify conventional constraint-based layouts with flow layouts, which enables the definition of flexible layouts that adapt to…
Learning Generative Models using Denoising Density Estimators
Siavash A. Bigdeli, Geng Lin, Tiziano Portenier +2
Learning probabilistic models that can estimate the density of a given set of samples, and generate samples from that density, is one of the fundamental challenges in unsupervised…