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FCSS: Fully Convolutional Self-Similarity for Dense Semantic Correspondence

Research article (2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017) · cited 130× · AI/ML
academia openalex:W2593948489
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FCSS: Fully Convolutional Self-Similarity for Dense Semantic Correspondence

Summary

FCSS: Fully Convolutional Self-Similarity for Dense Semantic Correspondence is a scholarly article[1].

Key Facts

  • FCSS: Fully Convolutional Self-Similarity for Dense Semantic Correspondence's instance of is recorded as scholarly article[2].

References

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA 4ort.xyz Knowledge Graph. (2026). FCSS: Fully Convolutional Self-Similarity for Dense Semantic Correspondence. Retrieved May 24, 2026, from https://4ort.xyz/entity/fcss-fully-convolutional-self-similarity-for-dense-semantic-correspondence
MLA “FCSS: Fully Convolutional Self-Similarity for Dense Semantic Correspondence.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/fcss-fully-convolutional-self-similarity-for-dense-semantic-correspondence.
BibTeX @misc{4ortxyz_fcss-fully-convolutional-self-similarity-for-dense-semantic-correspondence_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{FCSS: Fully Convolutional Self-Similarity for Dense Semantic Correspondence}}, year = {2026}, url = {https://4ort.xyz/entity/fcss-fully-convolutional-self-similarity-for-dense-semantic-correspondence}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): FCSS: Fully Convolutional Self-Similarity for Dense Semantic Correspondence — https://4ort.xyz/entity/fcss-fully-convolutional-self-similarity-for-dense-semantic-correspondence (retrieved 2026-05-24)

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