163 citations · 279 across the 17 of their papers we have counts for
5 papers · 1 filter
Multi-column Point-CNN for Sketch Segmentation
Fei Wang, Shujin Lin, Hanhui Li +4
Traditional sketch segmentation methods mainly rely on handcrafted features and complicate models, and their performance is far from satisfactory due to the abstract representation…
Neural Task Planning with And-Or Graph Representations
Tianshui Chen, Riquan Chen, Lin Nie +3
This paper focuses on semantic task planning, i.e., predicting a sequence of actions toward accomplishing a specific task under a certain scene, which is a new problem in computer…
Fine-Grained Representation Learning and Recognition by Exploiting Hierarchical Semantic Embedding
Tianshui Chen, Wenxi Wu, Yuefang Gao +3
Object categories inherently form a hierarchy with different levels of concept abstraction, especially for fine-grained categories. For example, birds (Aves) can be categorized acc…
Knowledge-Embedded Representation Learning for Fine-Grained Image Recognition
Tianshui Chen, Liang Lin, Riquan Chen +2
Humans can naturally understand an image in depth with the aid of rich knowledge accumulated from daily lives or professions. For example, to achieve fine-grained image recognition…
Structured Inhomogeneous Density Map Learning for Crowd Counting
Hanhui Li, Xiangjian He, Hefeng Wu +4
In this paper, we aim at tackling the problem of crowd counting in extremely high-density scenes, which contain hundreds, or even thousands of people. We begin by a comprehensive a…