RBCN: Rectified binary convolutional networks for enhancing the performance of 1-bit DCNNs

Chunlei Liu, Wenrui Ding, Xin Xia, Yuan Hu, Baochang Zhang, Jianzhuang Liu, Bohan Zhuang, Guodong Guo

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

5 Citations (Scopus)

Abstract

Binarized convolutional neural networks (BCNNs) are widely used to improve memory and computation efficiency of deep convolutional neural networks (DCNNs) for mobile and AI chips based applications. However, current BCNNs are not able to fully explore their corresponding full-precision models, causing a significant performance gap between them. In this paper, we propose rectified binary convolutional networks (RBCNs), towards optimized BCNNs, by combining full-precision kernels and feature maps to rectify the binarization process in a unified framework. In particular, we use a GAN to train the 1-bit binary network with the guidance of its corresponding full-precision model, which significantly improves the performance of BCNNs. The rectified convolutional layers are generic and flexible, and can be easily incorporated into existing DCNNs such as WideResNets and ResNets. Extensive experiments demonstrate the superior performance of the proposed RBCNs over state-of-the-art BCNNs. In particular, our method shows strong generalization on the object tracking task.

Original languageEnglish
Title of host publicationProceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence
EditorsSarit Kraus
Place of PublicationMarina del Rey CA USA
PublisherAssociation for the Advancement of Artificial Intelligence (AAAI)
Pages854-860
Number of pages7
ISBN (Electronic)9780999241141
DOIs
Publication statusPublished - 2019
Externally publishedYes
EventInternational Joint Conference on Artificial Intelligence 2019 - Macao, China
Duration: 10 Aug 201916 Aug 2019
Conference number: 28th
https://ijcai19.org/
https://www.ijcai.org/proceedings/2019/ (Proceedings)

Conference

ConferenceInternational Joint Conference on Artificial Intelligence 2019
Abbreviated titleIJCAI 2019
CountryChina
CityMacao
Period10/08/1916/08/19
Internet address

Keywords

  • Computer Vision
  • Motion and Tracking

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