*PFPN AAAI2020 aaai.org Pytorch Usage # model_name: lower-cased method name. E.g. poolnet, egnet, gcpa, dhsnet or minet. python3 train.py model_name --gpus=0 --trset=[DUTS-TR,SALOD,COD-TR] python3 test.py model_name --gpus=0 --weight=path_to_weight [--save] python3 test_...
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Mask R-CNN for Object Detection and Segmentation This is an implementation of Mask R-CNN on Python 3, Keras, and TensorFlow based on Matterport's version. The model generates bounding boxes and segmentation masks for each instance of an object in the image, with Feature Pyramid Network (FPN)...
e.g., polyps in a screening colonoscopy. Thereby, the endoscopist examines the large intestine (colon) with a long flexible tube that is inserted into the rectum. A small camera is mounted at the end of the tube, enabling the physician to look...
PzrS$IVF||aU4~W z7=JUR7gqHa?mO6>XjtZFECA%a6@d`6_`HTt^}up=N<=(7udmfm6*c8zqrjSmc2MjE z)D%rT#Y9^Fj@yCOW}8ykH`bb}F!rJ-Pc^AJ&7fpn>AidHiDAaeJ&fNy8t!inBuw}F zPy$qUEVpPN7t$~NOsCaCIR1r}l^6~&6cn$I13KymHElt+J1x`Wh}4=*PE$9z-z+t_ zNroTg)^00LY8*w6x-ZM=5&...
torchpack dist-run -np 2 python tools/test.py configs/nuscenes/det/transfusion/secfpn/camera+lidar/swint_v0p075/convfuser.yaml pretrained/bevfusion-det.pth --eval bbox However when running the following to evaluate the segmentations I get the output and error below. I have a 72 core dual...
to the state of the art, while being orders of magnitude faster to compute than other architectures that achieve top precision. The resulting tradeoff makes our model an ideal approach for scene understanding in IV applications. The code is publicly available at:https://github.com/Eromera/erfnet...
ASTS_Weakly [paper] ResNet101-FPN 65.3 84.2 2.5 TIP2020 Boundary [paper] ResNet50-FPN 65.0 76.1 - AAAI2020 ABCNet [paper] ResNet50-FPN 64.2 75.7 17.9 CVPR2020 CAPNet [paper] ResNet50-FPN 62.7 - - ICASSP2020 Feng et al. [paper] VGG 55.8 79.2 - IJCV2020 TextNet [paper] ResNet50...
6 0.848 0.979 0.960 -1.0 -1.0 0.848 0.995671 0.996 0.067540 0.170206 35.0 7 0.846 0.979 0.960 -1.0 -1.0 0.846 0.995671 0.996 0.057506 0.158793 40.0 8 0.852 0.979 0.960 -1.0 -1.0 0.852 0.997783 0.998 0.069616 0.170459 45.0 9 0.848 0.979 0.960 -1.0 -1.0 0.848 0.998878 0.999 0.063433 0.165182 50...
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