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Neural Points: Point Cloud Representation with Neural Fields

Dec 13, 2021
Wanquan Feng, Jin Li, Hongrui Cai, Xiaonan Luo, Juyong Zhang

* Project page: 

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GAN for Vision, KG for Relation: a Two-stage Deep Network for Zero-shot Action Recognition

May 25, 2021
Bin Sun, Dehui Kong, Shaofan Wang, Jinghua Li, Baocai Yin, Xiaonan Luo

* 19 pages, 7 figures 

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Neural Task Planning with And-Or Graph Representations

Aug 25, 2018
Tianshui Chen, Riquan Chen, Lin Nie, Xiaonan Luo, Xiaobai Liu, Liang Lin

* Submitted to TMM, under minor revision. arXiv admin note: text overlap with arXiv:1707.04677 

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Fine-Grained Representation Learning and Recognition by Exploiting Hierarchical Semantic Embedding

Aug 14, 2018
Tianshui Chen, Wenxi Wu, Yuefang Gao, Le Dong, Xiaonan Luo, Liang Lin

* Accepted at ACM MM 2018 as oral presentation 

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Learning to Segment Object Candidates via Recursive Neural Networks

Jul 29, 2018
Tianshui Chen, Liang Lin, Xian Wu, Nong Xiao, Xiaonan Luo

* Accepted at TIP 

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Knowledge-Embedded Representation Learning for Fine-Grained Image Recognition

Jul 02, 2018
Tianshui Chen, Liang Lin, Riquan Chen, Yang Wu, Xiaonan Luo

* Accepted at IJCAI 2018. The first work that introduces high-level knowledge to enhance representation learning for fine-grained image classification 

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Structured Inhomogeneous Density Map Learning for Crowd Counting

Jan 20, 2018
Hanhui Li, Xiangjian He, Hefeng Wu, Saeed Amirgholipour Kasmani, Ruomei Wang, Xiaonan Luo, Liang Lin

* 10 pages, 7 figures 

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Learning Deep Similarity Models with Focus Ranking for Fabric Image Retrieval

Dec 29, 2017
Daiguo Deng, Ruomei Wang, Hefeng Wu, Huayong He, Qi Li, Xiaonan Luo

* 11 pages, 9 figures, accepted by Image and Vision Computing 

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Learning a Wavelet-like Auto-Encoder to Accelerate Deep Neural Networks

Dec 20, 2017
Tianshui Chen, Liang Lin, Wangmeng Zuo, Xiaonan Luo, Lei Zhang

* Accepted at AAAI 2018 

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DISC: Deep Image Saliency Computing via Progressive Representation Learning

Dec 10, 2015
Tianshui Chen, Liang Lin, Lingbo Liu, Xiaonan Luo, Xuelong Li

* This manuscript is the accepted version for IEEE Transactions on Neural Networks and Learning Systems (T-NNLS), 2015 

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