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BEST PAPER AWARDS


Best Industry Related Paper Award (BIRPA)
This award is administrated by the IAPR Industrial Liaison Committee and its primary purpose is to acknowledge and encourage excellence research with potential for viable commercial impact.  The award is derived from the general “Prizes and Awards” budget of IAPR and a suitably inscribed certificate. If the paper wishes to be nominated for this award, one of the authors listed in the paper must have industrial affiliation.

We are happy to announce that the Best Industry Related Paper Award in ICPR 2018 is given to the following paper:
Zhengyuan Yang, Yixuan Zhang, Jerry Yu, Junjie Cai and Jiebo Luo, End-to-end Multi-Modal Multi-Task Vehicle Control for Self-Driving Cars with Visual Perceptions.



Piero Zamperoni Best Student Paper Award (PZBSPA)
The primary purpose of this award is to acknowledge and encourage excellence in pattern recognition research by students, and to help assure the future livelihood of the field. The award also honors the memory of Dr. Piero Zamperoni, an outstanding educator in pattern recognition. Eligibility for the award is restricted to papers authored or co-authored by a student. There must be no more than two authors, and if only one author of a co-authored paper is a student, then the other author must certify that the work presented in the paper is primarily the work of the student. The student author must have been a registered student at the time of paper submission. The Award consists of some cash reward and a suitably inscribed certificate.

We are happy to announce that the Piero Zamperoni Best Student Paper Award in ICPR 2018 is given to the following paper:
Kunkun Pang, Mingzhi Dong, Yang Wu and Timothy Hospedales, Dynamic Ensemble Active Learning: A Non-Stationary Bandit with Expert Advice.


Best Scientific Paper Award (BSPA)

Six best scientific paper awards, one for each ICPR Track, will be given to papers selected by the Technical Program Committee of ICPR. Each award consists of some cash reward and a suitably inscribed certificate.

We are happy to announce that the Best Scientific Paper Awards in ICPR 2018 are given to the following papers:
Zhihong Zhang, Da  Zhou, Chuanyu Xu, Beizhan, Wang; Dong Wang; Guijun REN, Edwin Hancock, Lu Bai and Lixin Cui, Depth-Based Subgraph Convolutional Neural Networks.
Jiyuan Zhang, Gang Zeng and Hongbin Zha, Scalable Monocular SLAM by Fusing and Connecting Line Segments with Inverse Depth Filter.
Jiedong Hao, Jing Zhang, Wei Wang and Tieniu Tan, DeepFirearm: Learning Discriminative Feature Representation for Fine-Grained Firearm Retrieval.
Qin Xu, Yifan Sun, Yali Li and Shengjin Wang, Attend and Align: Improving Deep Representations with Feature Alignment Layer for Person Retrieval.
Pau Riba, Andreas Fischer, Josep Llados and Alicia Fornés, Learning Graph Distances with Message Passing Neural Networks.
Ashis Kumar Dhara,Erik Arvids, Markus Fahlstr?m, Johan Wikstr?m, Elna-Marie Larsson and Robin Strand, Interactive Segmentation of Glioblastoma for Post-Surgical Treatment Follow-Up.


Best Student Paper Awards (BSPA)

The awards are given to the best student paper in each of the six ICPR tracks to acknowledge and encourage excellence in research by students in all areas of Pattern Recognition, and to help assure the future livelihood and sustainability of the field. Eligibility for the award is restricted to papers authored or co-authored by a student who must have been a registered student at the time of paper submission.  Each of the Awards consists of some cash reward and a suitably inscribed certificate.

We are happy to announce that the Best Student Paper Award Awards in ICPR 2018 are given to the following papers:
Shan Xu, Xiao Zhang and Shizhong Liao, A Linear Incremental Nystrom Method for Online Kernel Learning.
Doris Antensteiner, Svorad Ttolc and Thoma Pock, Variational Fusion of Light Field and Photometric Stereo for Precise 3D Sensing within a Multi-Line Scan Framework
Pramuditha Perera, Abavisani Mahdi, and Vishal Patel, In2I : Unsupervised Multi-Image-to-Image Translation Using Generative Adversarial Networks.
Vishwanath Sindagi, Vishal Patel, and Xing Di, GP-GAN: Gender Preserving GAN for Synthesizing Faces from Landmarks.
Shailza Jolly, Brian Iwana, Ryohei Kuroki and Seiichi Uchida, How Do Convolutional Neural Networks Learn Design?
Daniel Lopez-Martinez, Ke Peng, Sarah Steele, Arielle Lee, David Borsook and Rosalind Picard, Multi-task Multiple Kernel Machines for Personalized Pain Recognition from Functional Near-Infrared Spectroscopy Brain Signals.