Faster R Cnn
Found 4 free book(s)
YOLOv3: An Incremental Improvement
pjreddie.comFaster R-CNN by G-RMI [6] Inception-ResNet-v2 [21] 34.7 55.5 36.7 13.5 38.1 52.0 Faster R-CNN w TDM [20] Inception-ResNet-v2-TDM 36.8 57.7 39.2 16.2 39.8 52.1 One-stage methods
Bottleneck Transformers for Visual Recognition
openaccess.thecvf.comnostic to the detection framework (be it DETR or R-CNN). We perform our experiments with the Mask [27] and Faster R-CNN [50] systems and leave it for future work to integrate BoTNet as the backbone in the DETR framework. With visibly good gains on small objects in BoTNet, we believe there maybe an opportunity to address the lack of gain on
FCOS: Fully Convolutional One-Stage Object Detection
openaccess.thecvf.comYOLOv3, and Faster R-CNN rely on pre-defined anchor boxes. In contrast, our proposed detector FCOS is anchor box free, as well as proposal free. By eliminating the pre-defined set of anchor boxes, FCOS completely avoids the complicated computation related to anchor boxes such as calculating overlapping during training. More importantly,
Faster R-CNN: Towards Real-Time Object Detection with ...
arxiv.orgFast R-CNN [2] enables end-to-end detector training on shared convolutional features and shows compelling accuracy and speed. 3 FASTER R-CNN Our object detection system, called Faster R-CNN, is composed of two modules. The first module is a deep fully convolutional network that proposes regions, and the second module is the Fast R-CNN detector [2]