Claim · 2015-06-04 · publication · Stated in source · Supported

The paper introduces a Region Proposal Network (RPN) that shares full-image convolutional features with the detection network, which the authors state makes region proposals nearly cost-free.

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What it connects

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks → states its contribution → The paper introduces a Region Proposal Network (RPN) that shares full-image convolutional features with the detection network, which the authors state makes region proposals nearly cost-free.

Where it appears

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Claim and evidence

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networksstates its contribution ↓The paper introduces a Region Proposal Network (RPN) that shares full-image convolutional features with the detection network, which the authors state makes region proposals nearly cost-free.

Machine-checked, not reviewed by an editorStated in sourceSupported

Supporting evidence: primary · 1 source

Date: 2015-06-04 · publication Records dated 2015 →

Scope and limitsThe paper's own description of its contribution; not an assessment of it.

The evidence 01

primary sourceSupports the claim

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

arXiv · 2015-06-04

Cite the original source

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Source excerpt

“In this work, we introduce a Region Proposal Network (RPN) that shares full-image convolutional features with the detection network, thus enabling nearly cost-free region proposals.”

Location in source arXiv v1, PDF p. 1, abstract

Machine-checked · 2026-10-31

Source details and check notes

Authors: Shaoqing Ren; Kaiming He; Ross Girshick; Jian Sun
Version: arXiv:1506.01497v1, submitted 4 June 2015 (UTC). Retrieved for the candidate pack on 2026-10-28 (SHA-256 9d72de197c6c8e76f32602fc447406d6a43f37b5b019933dd4d873463061a6ef). The author list is the byline as printed on the first page.
Version date: 2015-06-04
Canonical address: Open the canonical source ↗
Accessed: 2026-10-28
Language: English (en)
Attribution: Shaoqing Ren, Kaiming He, Ross Girshick, Jian Sun, “Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks”, 2015-06-04.
Reuse: No open redistribution licence asserted. Bibliographic metadata, editorial paraphrases and short attributed quotations (at most 50 words each). Recheck terms before wider redistribution.
Check notes: Candidate pack passage, key papers (research/key-papers). The quotation (25 words) matched the text retrieved for the candidate pack on 2026-10-28 (research/key-papers/verification.json). Matching ignored differences of whitespace, case, quotation marks, dashes and line-break hyphens, so the source’s typography can differ. No human editorial review.

Status and meaning

Editorial status. Not reviewed by an editor. An exploratory record that no editor has accepted. This status does not say whether a person has read any linked passage. Each evidence record above shows how it was checked.

Relation. A paper or other publication describes its own contribution, quoted from the expression the record names, usually its abstract or introduction. The record is the document’s own description, not an assessment: a claim of priority or novelty it contains is the document’s claim, flagged as such, and says nothing about earlier or later work.

Date. Date of the arXiv version quoted, submitted 4 June 2015 (UTC); later versions may word it differently.

Record ID kp-states-faster-r-cnn-towards-real-2015-1