The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Reasoning about Object Affordances in a Knowledge Base Representation
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Citations
Cites
ImageNet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017) · Communications of the ACM · doi:10.1145/3065386 · Cited by 112,155
ImageNet: A large-scale hierarchical image database
Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., & Fei-Fei, L. (2009) · 2009 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2009.5206848 · Cited by 65,333
Self-citationThe Ecological Approach to Visual Perception
Bornstein, M. H., & Gibson, J. J. (1980) · The Journal of Aesthetics and Art Criticism · doi:10.2307/429816 · Cited by 22,935
Describing objects by their attributes
Farhadi, A., Endres, I., Hoiem, D., & Forsyth, D. (2009) · 2009 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2009.5206772 · Cited by 1,917
Cited by
Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations
Krishna, R., Zhu, Y., Groth, O., Johnson, J., Hata, K., Kravitz, J., Chen, S., Kalantidis, Y., Li, L.-J., Shamma, D. A., et al. (2017) · International Journal of Computer Vision · doi:10.1007/s11263-016-0981-7 · Cited by 5,107
Self-citationNeural Motifs: Scene Graph Parsing with Global Context
Zellers, R., Yatskar, M., Thomson, S., & Choi, Y. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00611 · Cited by 1,052
Visual7W: Grounded Question Answering in Images
Zhu, Y., Groth, O., Bernstein, M., & Fei-Fei, L. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.540 · Cited by 794
“The proposed models range from probabilistic inference [27, 44, 51] and recurrent neural networks [1, 7, 28, 36] to convolutional networks [26].”
BackgroundSelf-citation3D Scene Graph: A Structure for Unified Semantics, 3D Space, and Camera
Armeni, I., He, Z.-Y., Zamir, A., Gwak, J., Malik, J., Fischer, M., & Savarese, S. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00576 · Cited by 350
Wang, T., Huang, J., Zhang, H., & Sun, Q. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.01077 · Cited by 291
Metadata
- Authors
- Zhu, Y., Fathi, A., & Fei-Fei, L.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2014
- Pages
- 408-424
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W1891689858
- Cited by
- 205
- References
- 4
- FWCI
- 36.57
- Type
- conference paper
- Language
- en
- Open access
- closed
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Cite CoChat for the checks on this page, and the paper for its own findings.
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- CoChat. (2026). Citation check: Reasoning about Object Affordances in a Knowledge Base Representation. https://app.cochat.ai/papers/10.1007/978-3-319-10605-2_27
- The paper
- Zhu, Y., Fathi, A., & Fei-Fei, L. (2014). Reasoning about Object Affordances in a Knowledge Base Representation. Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-319-10605-2_27
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
