Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
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nair, 0, Rectified linear units improve restricted Boltzmann machines, Proc 27th Int Conf Mach Learn, 807
zeiler, 0, Visualizing and understanding convolutional neural networks, Proc 13th Eur Conf Comput Vis, 818
chorowski, 0, Attention-based models for speech recognition, Proc Adv Neural Inform Process Syst, 577
ren, 2015, Object detection networks on convolutional feature maps, arXiv 1504 06066
hoiem, 0, Diagnosing error in object detectors, Proc 12th Eur Conf Comput Vis, 340
lin, 0, Microsoft COCO: Common objects in context, Proc Eur Conf Comput Vis, 740
song, 2015, Deep sliding shapes for amodal 3d object detection in RGB-D images, arXiv 1511 02300
zhu, 2015, DeePM: A deep part-based model for object detection and semantic part localization, arXiv 1511 07131
dai, 2015, Instance-aware semantic segmentation via multi-task network cascades, arXiv 1512 04412
johnson, 2015, Densecap: Fully convolutional localization networks for dense captioning, arXiv 1511 07571
kislyuk, 2015, Human curation and convnets: Powering item-to-item recommendations on pinterest, arXiv 1511 04003
he, 2015, Deep residual learning for image recognition, arXiv 1512 03385
hosang, 0, How good are detection proposals, really?, Proc Brit Mach Vis Conf
pinheiro, 0, Learning to segment object candidates, Proc Adv Neural Inform Process Syst, 1981
szegedy, 2015, Scalable, high-quality object detection, arXiv 1412 1441
simonyan, 0, Very deep convolutional networks for large-scale image recognition, Proc Int Conf Learn Representations
zitnick, 0, Edge boxes: Locating object proposals from edges, Proc 13th Eur Conf Comput Vis, 391
sermanet, 0, Overfeat: Integrated recognition, localization and detection using convolutional networks, Proc Int Conf Learn Representations
he, 0, Spatial pyramid pooling in deep convolutional networks for visual recognition, Proc 13th Eur Conf Comput Vis, 346
chavali, 2015, Object-proposal evaluation protocol is 'gameable’, arXiv 1505 05836
szegedy, 0, Deep neural networks for object detection, Proc Neural Inform Process Syst