53 citations · 76 across the 4 of their papers we have counts for
4 papers
FETNet: Feature Erasing and Transferring Network for Scene Text Removal
Guangtao Lyu, Kun Liu, Anna Zhu +2
The scene text removal (STR) task aims to remove text regions and recover the background smoothly in images for private information protection. Most existing STR methods adopt enco…
FAME: 3D Shape Generation via Functionality-Aware Model Evolution
Yanran Guan, Han Liu, Kun Liu +8
We introduce a modeling tool which can evolve a set of 3D objects in a functionality-aware manner. Our goal is for the evolution to generate large and diverse sets of plausible 3D…
PartNet: A Recursive Part Decomposition Network for Fine-grained and Hierarchical Shape Segmentation
Fenggen Yu, Kun Liu, Yan Zhang +2
Deep learning approaches to 3D shape segmentation are typically formulated as a multi-class labeling problem. Existing models are trained for a fixed set of labels, which greatly l…
Large-Scale 3D Shape Reconstruction and Segmentation from ShapeNet Core55
Li Yi, Lin Shao, Manolis Savva +47
We introduce a large-scale 3D shape understanding benchmark using data and annotation from ShapeNet 3D object database. The benchmark consists of two tasks: part-level segmentation…