Large Scale High Quality Dataset For Object
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Learning Transferable Visual Models From Natural Language ...
proceedings.mlr.press2.1. Creating a Sufficiently Large Dataset Existing work has mainly used three datasets, MS-COCO (Lin et al.,2014), Visual Genome (Krishna et al.,2017), and YFCC100M (Thomee et al.,2016). While MS-COCO and Visual Genome are high quality crowd-labeled datasets, they are small by modern standards with approximately 100,000 training photos each.
Pre-Trained Image Processing Transformer
openaccess.thecvf.comto be excavated using large-scale dataset, we should pre-pair a great number of images with considerable diversity for training the IPT model. To this end, we select the Im-ageNet benchmark which contains various high-resolution with 1,000 categories. For each image in the ImageNet, we generate multiple corrupted counterparts using several
HigherHRNet: Scale-Aware Representation Learning for ...
openaccess.thecvf.comscale fusions between branches, HRNet [38, 40] can gener-ate high resolution feature maps with rich semantic. We adopt HRNet [38, 40] as our base network to gener-ate high-quality feature maps. And we add a deconvolution module to generate higher resolution feature maps to pre-dict heatmaps. The resulting model is named “Scale-Aware