Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 6,319

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope

Oliva, Aude, Torralba, Antonio·2001·International Journal of Computer Vision
DOI 10.1023/a:1011139631724
Open this paper in CoChat — free account

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1023/a:1011139631724

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 2 references

Research works printed but not linked: 47

  1. Amadasun, M. 1989. Textural features corresponding to textural properties. IEEE Trans. Sys., Man and Cybernetics, 19:1264-1274. · DOI · Paper page
  2. Atick, J. and Redlich, A. 1992. What does the retina know about natural scenes? Neural Computation, 4:196-210. · DOI · Paper page
  3. Baddeley, R. 1997. The correlational structure of natural images and the calibration of spatial representations. Cognitive Science, 21:351-372. · DOI
  4. Barrow, H.G. and Tannenbaum, J.M. 1978. Recovering intrinsec scene characteristics from images. In Computer Vision Systems, A. Hanson and E. Riseman (Eds.), Academic Press: New York, pp. 3-26.
  5. Biederman, I. 1988. Aspects and extension of a theory of human image understanding. In Computational Processes in Human Vision: An Interdisciplinary Perspective, Z. Pylyshyn (Ed.), Ablex Publishing Corporation: Norwood, New Jersey.
  6. Carson, C., Belongie, S., Greenspan, H., and Malik, J. 1997. Regionbased image querying. In Proc. IEEEW. on Content-Based Access of Image and Video Libraries, pp. 42-49. · doi:10.1109/ivl.1997.629719
  7. Carson, C., Thomas, M., Belongie, S., Hellerstein, J.M., and Malik, J. 1999. Blobworld: A system for region-based image indexing and retrieval. In Third Int. Conf. on Visual Information Systems, June 1999, Springer-Verlag. · DOI · Paper page
  8. De Bonet, J.S. and Viola, P. 1997. Structure driven image database retrieval. Advances in Neural Information Processing, 10:866-872.
  9. van der Schaaf, A. and van Hateren, J.H. 1996. Modeling of the power spectra of natural images: Statistics and information. Vision Research, 36:2759-2770. · DOI · Paper page
  10. Field, D.J. 1987. Relations between the statistics of natural images and the response properties of cortical cells. Journal of Optical Society of America, 4:2379-2394. · DOI · Paper page
  11. Field, D.J. 1994. What is the goal of sensory coding? Neural Computation, 6:559-601. · DOI · Paper page
  12. Friedman, A. 1979. Framing pictures: The role of knowledge in automatized encoding and memory for gist. Journal of Experimental Psychology: General, 108:316-355. · DOI · Paper page
  13. Guerin-Dugue, A. and Oliva, A. 2000. Classification of scene photographs from local orientations features. Pattern Recognition Letters, 21:1135-1140. · doi:10.1016/s0167-8655(00)00074-x
  14. Gorkani, M.M. and Picard, R.W. 1994. Texture orientation for sorting photos “at a glance”. In Proc. Int. Conf. Pat. Rec., Jerusalem, Vol. I, pp. 459-464.
  15. Hancock, P.J., Baddeley, R.J., and Smith, L.S. 1992. The principal components of natural images. Network, 3:61-70. · DOI
  16. Heaps, C. and Handel, S. 1999. Similarity and features of natural textures. Journal of Experimental Psychology: Human Perception and Performance, 25:299-320.
  17. Henderson, J.M. and Hollingworth, A. 1999. High level scene perception. Annual Review of Psychology, 50:243-271. · DOI · Paper page
  18. Hochberg, J.E. 1968. In the mind's eye. In Contemporary Theory and Research in Visual Perception, R.N. Haber (Ed.), Holt, Rinehart, and Winston: New York, pp. 309-331.
  19. Lipson, P., Grimson, E., and Sinha, P. 1997. Configuration based scene classification and image indexing. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Puerto Rico, pp. 1007-1013. · DOI
  20. Marr, D. 1982. Vision. WH Freeman: San Francisco, CA.
  21. Moghaddam, B. and Pentland, A. 1997. Probabilistic Visual Learning for Object Representation. IEEE Trans. Pattern Analysis and Machine Vision, 19(7):696-710. · DOI · Paper page
  22. Morgan, M.J., Ross, J., and Hayes, A. 1991. The relative importance of local phase and local amplitude in patchwise image reconstruction. Biological Cybernetics, 65:113-119. · DOI
  23. Oliva, A. and Schyns, P.G. 1997. Coarse blobs or fine edges? Evidence that information diagnosticity changes the perception of complex visual stimuli. Cognitive Psychology, 34:72-107. · DOI · Paper page
  24. Oliva, A. and Schyns, P.G. 2000. Diagnostic color blobs mediate scene recognition. Cognitive Psychology, 41:176-210. · DOI · Paper page
  25. Oliva, A., Torralba, A., Guerin-Dugue, A., and Herault, J. 1999. Global semantic classification using power spectrum templates. In Proceedings of The Challenge of Image Retrieval, Electronic Workshops in Computing series, Springer-Verlag: Newcastle.
  26. O'Regan, J.K., Rensink, R.A., and Clark, J.J. 1999. Changeblindness as a result of 'mudsplashes'. Nature, 398:34. · DOI · Paper page
  27. Piotrowski, L.N. and Campbell, F.W. 1982. A demonstration of the visual importance and flexibility of spatial-frequency amplitude and phase. Perception, 11:337-346. · DOI
  28. Pentland, A.P. 1984. Fractal-based description of natural scenes. IEEE Trans. on Pattern Analysis and Machine Intelligence, 6:661-674. · DOI · Paper page
  29. Potter, M.C. 1975. Meaning in visual search. Science, 187:965-966. · DOI · Paper page
  30. Rao, A.R. and Lohse, G.L. 1993. Identifying high level features of texture perception. Graphical Models and Image Processing, 55:218-233. · DOI
  31. Rensink, R.A. 2000. The dynamic representation of scenes. Visual Cognition, 7:17-42. · DOI · Paper page
  32. Rensink, R.A., O'Regan, J.K., and Clark, J.J. 1997. To see or not to see: the need for attention to perceive changes in scenes. Psychological Science, 8:368-373. · DOI · Paper page
  33. Ripley, B.D. 1996. Pattern Recognition and Neural Networks. Cambridge University Press, Cambridge, UK. · DOI · Paper page
  34. Rosch, E. and Mervis, C.B. 1975. Family resemblances: Studies in the internal structure of categories. Cognitive Psychology, 7:573-605. · DOI · Paper page
  35. Sanocki, T. and Epstein, W. 1997. Priming spatial layout of scenes. Psychological Science, 8:374-378. · DOI
  36. Sanocki, T. and Reynolds, S. 2000. Does figural goodness influence the processing and representation of spatial layout. Investigative Ophthalmology and Visual Science, 41:723.
  37. Simons, D.J. and Levin, D.T. 1997. Change blindness. Trends in Cognitive Sciences, 1:261-267. · DOI · Paper page
  38. Sirovich, L. and Kirby, M. 1987. Low-dimensional procedure for the characterization of human faces. Journal of Optical Society of America, 4:519-524. · DOI · Paper page
  39. Swets, D.L. and Weng, J.J. 1996. Using discriminant eigenfeatures for image retrieval. IEEE Trans. On Pattern Analysis and Machine Intelligence, 18:831-836. · DOI · Paper page
  40. Switkes, E., Mayer, M.J., and Sloan, J.A. 1978. Spatial frequency analysis of the visual environment: anisotropy and the carpentered environment hypothesis. Vision Research, 18:1393-1399. · DOI · Paper page
  41. Szummer, M. and Picard, R.W. 1998. Indoor-outdoor image classification. In IEEE intl.Workshop on Content-Based Access of Image and Video Databases.
  42. Tamura, H., Mori, S., and Yamawaki, T. 1978. Textural features corresponding to visual perception. IEEE Trans. Sys. Man and Cybernetics, 8:460-473. · DOI · Paper page
  43. Torralba, A. and Oliva, A. 1999. Scene organization using discriminant structural templates. In IEEE Proc. Of Int. Conf in Comp. Vision, pp. 1253-1258. · doi:10.1109/iccv.1999.790424
  44. Torralba, A. and Sinha, P. 2001. Statistical context priming for object detection. In IEEE. Proc of Int. Conf. in Computer Vision.
  45. Tversky, B. and Hemenway, K. 1983. Categories of environmental scenes. Cognitive Psychology, 15:121-149. · DOI · Paper page
  46. Vailaya, A., Figueiredo, M., Jain, A., and Zhang, H.J. 1999. Contentbased hierarchical classification of vacation images. In Proceedings of the International Conference on Multimedia, Computing and Systems, June.
  47. Vailaya, A., Jain, A., and Zhang, H.J. 1998. On image classification: City images vs. landscapes. Pattern Recognition, 31:1921-1935. · DOI · Paper page

Cited by

See all 6,319

Metadata

Authors
Oliva, A., & Torralba, A.
Venue
International Journal of Computer Vision
Publisher
Springer Science and Business Media LLC
Published
2001-05
Volume
42
Issue
3
Pages
145-175
ISSN
  • 0920-5691 (ISSN-L)
  • 1573-1405
DOI
10.1023/a:1011139631724
OpenAlex
W1566135517
Cited by
6,319
References
2
FWCI
21.60
Type
journal article
Language
en
Open access
closed
Licence

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope. https://app.cochat.ai/papers/10.1023/a:1011139631724
The paper
Oliva, A., & Torralba, A. (2001). Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope. International Journal of Computer Vision. https://doi.org/10.1023/a%3A1011139631724

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.