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generate_anchors

Syntologyentry name in harvested coderead from the graph 2026-09-24

generate_anchors appears in the code Syntology harvested for 19 papers, as 16 distinct code bodies found in 23 places (a place is one code body under one paper). At least one of them ran in 2 of the papers; 1 of the code bodies carries a behaviour fingerprint.

What this page is not. Routines are grouped here by the exact string of their function or class name. Nothing asserts that two samples named generate_anchors do the same thing, share code, or are comparable; the name is a string, not an identity. Behaviour outputs (what a fingerprinted sample returned on the shared battery) are not in this export and are not shown here; the graph at syntology.ai holds them. "Ran" means executed on a synthesized fixture, not that the code is correct or reproduces a paper.

Samples Syntology

Syntology ran 2 of the 16 distinct code bodies named generate_anchors; 14 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
0ran · our draft was wrong
1ran · fixture could not drive it
1ran
14unverified
1fingerprinted

Licence is a property of each copy, so it is counted per place: 1 of the 23 places is pointer only (Syntology does not serve that copy's text). This site shows no code text for any sample; every row below links to the file in its repository where the record names one.

“Ran” means the sample executed on a synthesized input; it does not mean the output is correct. “Honoured” and “violated” refer to a contract Syntology drafted from the code itself; “our draft was wrong” and “fixture could not drive it” are failures of Syntology's instrument, not of the code, and those samples did run. The ran count above is every status except unverified, the same rule as each paper page.

Papers

19 papers shown of 19, newest first; 23 places in the table. A paper with no recorded date is placed by the month its arXiv id encodes, shown in the Date column as YYYY-MM (from id). One row per place: a paper whose repository defines the name more than once appears more than once, and the same code body held for several papers appears once under each, with the same status. Titles and dates are the archive's archive 2025-07-28 for papers in the archive, and the graph's for 1 papers added by Syntology; 1 papers have no page here and are shown by arXiv id only. Status and fingerprint are Syntology's record of each code body; licence is recorded for each place. The File cell ends with the code body's code_sha256, Syntology's identity for that exact code: an agent fetches the stored sample with Syntology's MCP tool get_code(code_sha256="…") (how to connect); click an identity to copy that call.

PaperDateFileStatus SyntologyLicence
Cross-Domain Object Detection Using Unsupervised Image Translation added by Syntology 2026-01 (from id) endernewton/tf-faster-rcnn/lib/layer_utils/generate_anchors.py d4f2ade15edff997 unverified MIT (permissive)
YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information 21 Feb 2024 WongKinYiu/YOLO/yolo/utils/bounding_box_utils.py 8e61071af5c8f65a ran MIT (permissive)
Versatile Multi-Modal Pre-Training for Human-Centric Perception 25 Mar 2022 hongfz16/hcmoco/A2J/anchor.py 90f11ad439eb9eac unverified MIT (permissive)
MonoDTR: Monocular 3D Object Detection with Depth-Aware Transformer 21 Mar 2022 kuanchihhuang/monodtr/visualDet3D/networks/heads/anchors.py 1279986e0f62b111 unverified MIT (permissive)
Deep Learning for Automatic Pneumonia Detection 28 May 2020 tatigabru/kaggle-rsna/src/pytorch_retinanet/anchors.py 1279986e0f62b111 unverified MIT (permissive)
Multiple Anchor Learning for Visual Object Detection 4 Dec 2019 DeLightCMU/MAL-inference/retinanet/box.py df48fc695a8a624c unverified BSD-2-Clause (permissive)
EfficientDet: Scalable and Efficient Object Detection 20 Nov 2019 toandaominh1997/EfficientDet.Pytorch/models/module.py 1279986e0f62b111 unverified MIT (permissive)
EfficientDet: Scalable and Efficient Object Detection 20 Nov 2019 signatrix/efficientdet/src/utils.py 5b3a9cef8ec8c746 unverified MIT (permissive)
CBNet: A Novel Composite Backbone Network Architecture for Object Detection 9 Sep 2019 PKUbahuangliuhe/CBNet/detectron/modeling/generate_anchors.py 7b2d56f403fb4468 unverified Apache-2.0 (permissive)
A2J: Anchor-to-Joint Regression Network for 3D Articulated Pose Estimation from a Single Depth Image 27 Aug 2019 bo-zhang-cs/CACNet-Pytorch/CACNet.py bb3c1b55b1637a8c unverified MIT (permissive)
RetinaFace: Single-stage Dense Face Localisation in the Wild 2 May 2019 code-trip/insightface-mxnet/python-package/insightface/model_zoo/face_detection.py 4b292d55fb7ca5d5 unverified MIT (permissive)
Clustered Object Detection in Aerial Images 16 Apr 2019 fyangneil/Clustered-Object-Detection-in-Aerial-Image/detectron/modeling/generate_anchors.py 7b2d56f403fb4468 unverified Apache-2.0 (permissive)
Differentiable Scene Graphs 26 Feb 2019 shikorab/DSG/lib/layer_utils/generate_anchors.py d4f2ade15edff997 unverified MIT (permissive)
Detecting Lesion Bounding Ellipses With Gaussian Proposal Networks 25 Feb 2019 baidu-research/GPN/model/generate_anchor.py 9c93db35eee3812e unverified Apache-2.0 (permissive)
Peeking into the Future: Predicting Future Person Activities and Locations in Videos 11 Feb 2019 JunweiLiang/social-distancing-prediction/code/inference/Object_Detection_Tracking/generate_anchors.py 97cd5f6189f39c1f unverified Apache-2.0 recorded; this copy not marked cleared · pointer only
Bounding Box Regression with Uncertainty for Accurate Object Detection 23 Sep 2018 yihui-he/KL-Loss/detectron/modeling/generate_anchors.py 7b2d56f403fb4468 unverified Apache-2.0 (permissive)
Feature Pyramid Networks for Object Detection 9 Dec 2016 adityaarun1/pytorch_fast-er_rcnn/lib/layer_utils/generate_anchors.py d4f2ade15edff997 unverified MIT (permissive)
Detecting Text in Natural Image with Connectionist Text Proposal Network 12 Sep 2016 Sanster/tf_ctpn/lib/layer_utils/generate_anchors.py 1ffc760a4459d409 unverified MIT (permissive)
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks 4 Jun 2015 facebookresearch/detectron/detectron/modeling/rpn_heads.py 08a5a1f47d119996 ran · fixture could not drive it fingerprinted Apache-2.0 (permissive)
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks 4 Jun 2015 jiajunhua/facebookresearch-Detectron/detectron/modeling/rpn_heads.py b77ffbba2e1a9d86 unverified Apache-2.0 (permissive)
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks 4 Jun 2015 aleksispi/drl-rpn-tf/lib/layer_utils/generate_anchors.py d4f2ade15edff997 unverified MIT (permissive)
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks 4 Jun 2015 WalterMa/gluon-faster-rcnn/rcnn/utils.py ffec5c8e487649a5 unverified MIT (permissive)
arXiv:Guo_Knowledge_Distillation_for_6D_Pose_Estimation_by_Aligning_Distributions_of_CVPR_2023_paper GUOShuxuan/kd-6d-pose-adlp/models/model.py 1960b9f6797229c5 unverified Apache-2.0 (permissive)

This site shows no code text; each File cell links to the file on GitHub at the repository's current default branch, which may have changed since the harvest. "Pointer only" means Syntology does not serve that copy's text, for one of four reasons: no licence file was found; the licence was not identified; the licence is recorded as permissive but that copy's record is not marked cleared; or the licence is outside the permissive list Syntology serves text under (MIT, Apache-2.0, BSD and similar). Some licences outside that list permit redistribution, such as WTFPL, and GPL-3.0 under its conditions; they are simply not on the list. Hover a licence cell for the reason. Per-sample records for a paper are on its paper page under "Code Syntology ran".

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