Coarse semantic segmentation results of the PASCAL VOC dataset based on the FCN and DeepLab-CRF model.Kai, QiaoJian, ChenLinyuan, WangLei, ZengBin, Yan
The Pascal Visual Object Classes (VOC) challenge is a benchmark in visual object category recognition and detection, providing the vision and machine learning communities with a standard dataset of images and annotation, and standard evaluation procedures. Organised annually from 2005 to present, the ...
The Pascal Visual Object Classes (VOC) challenge consists of two components: (i)a publicly available dataset of images together with ground truth annotation and standardised evaluation software; and (ii)an annual competition and workshop. There are five challenges: classification, detection, segmentatio...
we study a method to learn the model architectures directly on the dataset of interest. As this approach is expensive when the dataset is large, we propose to search for an architectural building block on a small dataset and then transfer the block to a larger dataset...
The Pascal Visual Object Classes (VOC) challenge is a benchmark in visual object category recognition and detection, providing the vision and machine learning communities with a standard dataset of images and annotation, and standard evaluation procedures. Organised annually from 2005 to present, the ...
We demonstrate the effectiveness of the method by showing substantially improved intersection-overunion segmentation scores on the Pascal VOC dataset using a state-of-the-art deep learning segmentation architecture. 展开 关键词: Computer Science - Computer Vision and Pattern Recognition ...
|->VOC2007TEST/ | |->Annotations/ | |->... VOCROOT is your path of the Pascal VOC Dataset. Run the following script to generate TFRecords. python dataset/convert_tfrecords.py --dataset_directory=VOCROOT --output_directory=./dataset/tfrecords Download the pre-trained VGG-16 model (...
EMANet-101 gets80.99on the PASCAL VOC dataset (Thanks for Sensetimes' server). So, with a classic backbone(ResNet) instead of some newest ones(WideResNet, HRNet), EMANet still achieves the top performance. EMANet-101 (OHEM) gets81.14in mIoU on Cityscapes val using single-scale inference, ...
PASCAL_VOC_IMAGES_DIR: Set this to the JPEGImages directory of the PascalVOC dataset.This variable is required for training for DAVIS and YouTube-VIS. MAPILLARY_IMAGES_DIR: You will need to do two extra things here: (1) Put all the training and validation images into a single directory ...
Pytorch >= 1.1.0 Python-Libs, e.g., cv2, skimage. Training Prepare your dataset. In our experiments, we used thePascalVocdataset to generate training data for Gaussian noise removal. Generate Gaussian or Poisson noise via skimage-lib. ...