Object proposal by multi-branch hierarchical segmentation
By Chaoyang Wang, Long Zhao, Shuang Liang, Liqing Zhang, Jinyuan Jia, Yichen Wei. 2015
40 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Luc Van Gool
- Xiaogang Wang
- Yi Yang
- Dacheng Tao
- Trevor Darrell
- Abhinav Kumar Gupta
- Lorenzo Torresani
- Jitendra Malik
Citations in the corpus
- Object-Proposal Evaluation Protocol is ‘Gameable’ (2015, neutral): “These methods include [2, 3, 6–9, 11, 44, 46, 49].”
- Self-taught object localization with deep networks (2014, methodology): “Objectness methods [2, 6, 30, 4, 3, 16, 36, 25, 21, 26, 32, 14] aim at generating bounding boxes that yield high recall for a high number of candidates, i.”
- Semantic Graph Convolutional Networks for 3D Human Pose Regression (2019, background): “Convolutional Neural Networks (CNNs) have successfully tackled classic computer vision problems such as image classification [12, 29, 31, 52], object detection [19, 46, 55, 63, 74, 79] and generation [43, 58, 71, 73, 80], where the input image has a grid-like structure.”