IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) is a scholarly archival journal published monthly. This journal covers traditional areas of computer vision and image understanding, all traditional areas of pattern analysis and recognition, and selected areas of machine intelligence. Read the full scope of TPAMI.
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From the May 2018 issue
Learning Compositional Sparse Bimodal Models
By Suren Kumar, Vikas Dhiman, Parker A. Koch, and Jason J. Corso
Various perceptual domains have underlying compositional semantics that are rarely captured in current models. We suspect this is because directly learning the compositional structure has evaded these models. Yet, the compositional structure of a given domain can be grounded in a separate domain thereby simplifying its learning. To that end, we propose a new approach to modeling bimodal perceptual domains that explicitly relates distinct projections across each modality and then jointly learns a bimodal sparse representation. The resulting model enables compositionality across these distinct projections and hence can generalize to unobserved percepts spanned by this compositional basis. For example, our model can be trained on red triangles and blue squares; yet, implicitly will also have learned red squares and blue triangles. The structure of the projections and hence the compositional basis is learned automatically; no assumption is made on the ordering of the compositional elements in either modality. Although our modeling paradigm is general, we explicitly focus on a tabletop building-blocks setting. To test our model, we have acquired a new bimodal dataset comprising images and spoken utterances of colored shapes (blocks) in the tabletop setting. Our experiments demonstrate the benefits of explicitly leveraging compositionality in both quantitative and human evaluation studies.
Editorials and Announcements
- TPAMI now offers authors access to Code Ocean. Code Ocean is a cloud-based executable research platform that allows authors to share their algorithms in an effort to make the world’s scientific code more open and reproducible. Learn more or sign up for free.
- We are pleased to announce that Sven Dickinson, a professor in the Department of Computer Science at the University of Toronto, Canada, has been named the new Editor-in-Chief of the IEEE Transactions on Pattern Analysis and Machine Intelligence starting in 2017.
- According to Clarivate Analytics' 2016 Journal Citation Report, TPAMI has an impact factor of 8.329.
- State of the Journal (Jan 2018)
- Incoming EIC Editorial (Jan 2017)
- State of the Journal (Jan 2017)
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- State of the Journal (Jan 2015)
- Editor's Note (June 2013)
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- State of the Journal (January 2012)
- Guest Editors' Introduction to the Special Section on Learning with Shared Information for Computer Vision and Multimedia Analysis (May 2018)
- Best of CVPR 2015 (April 2017)
- Special Issue on Multimodal Human Pose Recovery and Behavior Analysis (August 2016)
- Special Section on CVPR 2014 (July 2016)
- Special Section on CVPR 2013 (April 2016)
- Special Issue on Higher Order Graphical Models in Computer Vision (July 2015)
- Special Issue on Bayesian Nonparametrics (Feb 2015)
- TPAMI CVPR Special Section (Dec 2013)
- Special Section on Learning Deep Architectures (Aug 2013)
- In Memoriam: Mark Everingham (Nov 2012)
- Introduction to the Special Section on IEEE Conference on Computer Vision and Pattern Recognition (September 2012)
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