355 citations · 2.9k across the 115 of their papers we have counts for
8 papers · 1 filter
Hierarchical Point-Edge Interaction Network for Point Cloud Semantic Segmentation
Li Jiang, Hengshuang Zhao, Shu Liu +3
We achieve 3D semantic scene labeling by exploring semantic relation between each point and its contextual neighbors through edges. Besides an encoder-decoder branch for predicting…
Fast Point R-CNN
Yilun Chen, Shu Liu, Xiaoyong Shen +1
We present a unified, efficient and effective framework for point-cloud based 3D object detection. Our two-stage approach utilizes both voxel representation and raw point cloud dat…
STD: Sparse-to-Dense 3D Object Detector for Point Cloud
Zetong Yang, Yanan Sun, Shu Liu +2
We present a new two-stage 3D object detection framework, named sparse-to-dense 3D Object Detector (STD). The first stage is a bottom-up proposal generation network that uses raw p…
Landmark Assisted CycleGAN for Cartoon Face Generation
Ruizheng Wu, Xiaodong Gu, Xin Tao +3
In this paper, we are interested in generating an cartoon face of a person by using unpaired training data between real faces and cartoon ones. A major challenge of this task is th…
Attribute-Driven Spontaneous Motion in Unpaired Image Translation
Ruizheng Wu, Xin Tao, Xiaodong Gu +2
Current image translation methods, albeit effective to produce high-quality results in various applications, still do not consider much geometric transform. We in this paper propos…
Region Refinement Network for Salient Object Detection
Zhuotao Tian, Hengshuang Zhao, Michelle Shu +4
Albeit intensively studied, false prediction and unclear boundaries are still major issues of salient object detection. In this paper, we propose a Region Refinement Network (RRN),…
Associatively Segmenting Instances and Semantics in Point Clouds
Xinlong Wang, Shu Liu, Xiaoyong Shen +2
A 3D point cloud describes the real scene precisely and intuitively.To date how to segment diversified elements in such an informative 3D scene is rarely discussed. In this paper,…
Human Pose Estimation with Spatial Contextual Information
Hong Zhang, Hao Ouyang, Shu Liu +4
We explore the importance of spatial contextual information in human pose estimation. Most state-of-the-art pose networks are trained in a multi-stage manner and produce several au…