2 papers
cs.GR2018
SAGNet:Structure-aware Generative Network for 3D-Shape Modeling
Zhijie Wu, Xiang Wang, Di Lin +3
We present SAGNet, a structure-aware generative model for 3D shapes. Given a set of segmented objects of a certain class, the geometry of their parts and the pairwise relationships…
cs.CV2016
ScribbleSup: Scribble-Supervised Convolutional Networks for Semantic Segmentation
Di Lin, Jifeng Dai, Jiaya Jia +2
Large-scale data is of crucial importance for learning semantic segmentation models, but annotating per-pixel masks is a tedious and inefficient procedure. We note that for the top…