Faster R-CNN在COCO test-dev数据集上的mAP@.5是42.1%,比Fast R-CNN高2.8%;mAP@[.5,.95]的mAP@[.5,.95]是21.5%,比Fast R-CNN高2.2%。可以看到:Faster R-CNN的效果要优于Fast R-CNN,也说明了RPN网络的Excellent Performance. 评估指标mAP 论文中经常用mAP去衡量目标检测模型的好坏优劣,mAP的全称是Me...
Object Detection on COCO test-dev(M: Multi-Scale Testing with Shorter Side {480, 576, 688, 864, 1200, 1400}, B: Iterative Bounding Box Average) Using Deformable ConvNet consistently outperforms the plain one. WithAligned-Inception-ResNet, usingR-FCNwithDeformable Co...
Efficient:CenterNet-HarDNet85 model achieves44.3COCO mAP (test-dev) while running at45FPS on an NVIDIA GTX-1080Ti GPU. State of The Art:CenterNet-HarDNet85's is faster than YOLOv4, SpineNet-49, and EfficientDet-D2 Main results Object Detection on COCO validation ...
Our DLA-34 model runs at 52 FPS with 37.4 COCO AP. Strong: Our best single model achieves 45.1AP on COCO test-dev. Easy to use: We provide user friendly testing API and webcam demos. Main results Object Detection on COCO validation BackboneAP / FPSFlip AP / FPSMulti-scale AP / FPS...
我们将所提出的RefineDet方法在PASCAL VOC 2007测试集、PASCAL VOC 2012测试集和MS COCO test-dev测试集上的完整目标检测结果分别显示在表5、表6和表7中。在所有已发表的方法的结果中,我们的RefineDet在这三个检测数据集上,即, PASCAL VOC 2007测试集的mAP为85.8%,PASCAL VOC 2012测试集的mAP为86.8%,MS COCO ...
我们测试了不同的训练改进在 ImageNet 数据集分类任务 (ILSVRC 2012 年 val)和 MS COCO(test-dev 2017)数据集检测上 的准确性。 4.1. Experimental setup 实验设置 在ImageNet 的图像分类实验中,默认超参数如下:训练步数为 8 百万次;批大小和 mini 批大小分别为 128 和 32;polynomial decay learning rate sch...
dataset TT100K with 512 x 512 input, outperforming other detectors with a large margin. Moreover, it can also achieve state-of-the-art results for general object detection on PASCAL VOC2007 test and MS COCO test-dev2015, especially achieving 2 to 5 points improvement on small object ...
intro: one stage 43.2% on COCO test-dev arXiv: https://arxiv.org/abs/1901.08043 github: https://github.com/xingyizhou/ExtremeNet ORSIm Detector: A Novel Object Detection Framework in Optical Remote Sensing Imagery Using Spatial-Frequency Channel Features intro: IEEE TRANSACTIONS ON GEOSCIENCE AND...
Object metadata is a set of name-value pairs that describe the object and is used for object management.Currently, only the metadata defined by the system is supported. T
This API downloads an object as a file from OBS to your local computer.To download an object, you must be the bucket owner or have the required permission (obs:object:Get