Papers › Fast R-CNN

Fast R-CNN

30 Apr 2015ICCV 2015 12arXiv:1504.08083archive 2025-07-28

Ross Girshick

This paper proposes a Fast Region-based Convolutional Network method (Fast R-CNN) for object detection. Fast R-CNN builds on previous work to efficiently classify object proposals using deep convolutional networks. Compared to previous work, Fast R-CNN employs several innovations to improve training and testing speed while also increasing detection accuracy. Fast R-CNN trains the very deep VGG16 network 9x faster than R-CNN, is 213x faster at test-time, and achieves a higher mAP on PASCAL VOC 2012. Compared to SPPnet, Fast R-CNN trains VGG16 3x faster, tests 10x faster, and is more accurate. Fast R-CNN is implemented in Python and C++ (using Caffe) and is available under the open-source MIT License at https://github.com/rbgirshick/fast-rcnn.

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30 repositories listed; official and paper-mentioned ones first.

rbgirshick/fast-rcnn officialmentioned in papermentioned on GitHubcaffe2NOASSERTION report
BlackAngel1111/Fast-RCNN mentioned on GitHubcaffe2NOASSERTION report
FL77N/Fast-RCNN-on-PPDet mentioned on GitHubpaddle report
Qinhj07/ATOMCode mentioned on GitHubpytorch report
beassssry/U mentioned on GitHubcaffe2NOASSERTION report
devsoft123/fast-cnn mentioned on GitHubcaffe2NOASSERTION report
facebookresearch/detectron mentioned on GitHubpytorch report
jiajunhua/facebookresearch-Detectron mentioned on GitHubcaffe2 report
macomino/TFM mentioned on GitHubtf report
mrnabati/RRPN mentioned on GitHubcaffe2 report
msuhail1997/Fast-RCNN-Pytorch mentioned on GitHubpytorch report
qq330488563/TEST mentioned on GitHubcaffe2NOASSERTION report
rajs25/Object-Detection mentioned on GitHubtf report
rh01/fast-rnn mentioned on GitHubcaffe2 report
sbetageri/MaskRCNN mentioned on GitHubpytorchMIT report
serengil/retinaface mentioned on GitHubtf report
sunhui1234/haha mentioned on GitHubcaffe2NOASSERTION report
xjnpark/ds mentioned on GitHubcaffe2NOASSERTION report
zjZSTU/Fast-R-CNN mentioned on GitHubpytorch report

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2ran · our draft was wrong
1ran · fixture could not drive it
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ROI_Pool zjZSTU/Fast-R-CNN/py/models/vgg16_roi.py community (archive-listed) ran fingerprinted Apache-2.0 (permissive) · 26f153de51efe17c · report
VGG16_RoI zjZSTU/Fast-R-CNN/py/models/vgg16_roi.py community (archive-listed) ran Apache-2.0 (permissive) · fe710a62ca902ab4 · report
class_indices bmstu-iu8-g1-2019-project/road-signs-recognition/sources/detector/detector.py community (archive-listed) ran · our draft was wrong fingerprinted MIT (permissive) · 4f0b88a82728e9d8 · report
cpu_nms serengil/retinaface/retinaface/commons/postprocess.py community (archive-listed) ran · fixture could not drive it MIT (permissive) · 03e0b25aa5a59339 · report
on_index_wrapper bmstu-iu8-g1-2019-project/road-signs-recognition/sources/detector/detector.py community (archive-listed) ran · our draft was wrong MIT (permissive) · 370b7a5120a43be6 · report
add_fast_rcnn_outputs mrnabati/RRPN/detectron/detectron/modeling/fast_rcnn_heads.py community (archive-listed) unverified MIT (permissive) · 42384bd3a48004e8 · report
create_detector_model bmstu-iu8-g1-2019-project/road-signs-recognition/sources/detector/detector.py community (archive-listed) unverified MIT (permissive) · af5421ea89189612 · report
prepare_roidb rh01/fast-rnn/lib/roi_data_layer/roidb.py community (archive-listed) unverified licence not identified · pointer only · 432429bede769b4d · report

Tasks

ObjectObject Detection

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Object Detection PASCAL VOC 2007 Fast R-CNN MAP 70.0% #22 of 30 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

Methods

Introduced by this paper: Fast R-CNN

ConvolutionFast R-CNNRoIPoolSPEEDSoftmax

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