Learning Context-Sensitive Shape Similarity by Graph Transduction
By Xiang Bai, Xingwei Yang, Longin Jan Latecki, Zhuowen Tu. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010
308 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition
View Paper: https://www.semanticscholar.org/paper/dac4d7693b2c28d9791c0131e8d0d2082cfed79e
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
- Yi Yang
- Dacheng Tao
- Ming-Hsuan Yang
- Ming-Ming Cheng
- Xiaogang Wang
- Alan L. Yuille
- Qi Tian
Citations in the corpus
- Non-Rigid Point Set Registration by Preserving Global and Local Structures (2015, background): “Many tasks in these fields – such as stereo matching, image registration and shape recognition – can be formulated as a point set registration problem, which requires addressing two issues: find pointto-point correspondences and estimate the underlying spatial transformation which best aligns the tw”
- Robust Feature Matching for Remote Sensing Image Registration via Locally Linear Transforming (2015, background): “[12]–[15], image analysis [16]–[20], and particularly in the field of remote sensing [1], [21]–[24].”
- Scalable Person Re-identification on Supervised Smoothed Manifold (2017, background): “, manifold ranking [67], graph transduction [7]) totally ignore the beneficial influence from the labeled training data.”
- Is Rotation a Nuisance in Shape Recognition? (2014, methodology): “Please see [1] and [7] for the other four algorithms.”
- A Multimedia Retrieval Framework Based on Semi-Supervised Ranking and Relevance Feedback (2012, background): “During recent years, MR has been applied to various applications by other researchers, and the results on different applications, including image retrieval [15], shape retrieval [2], and cross-media retrieval [46], have demonstrated that it is beneficial to utilize the data distribution for ranking.”
- Global Contrast Based Salient Region Detection (2015, methodology): “MPEG-7 dataset, state-of-the-art methods can achieve 91:61 percent retrieval rates [58].”