Deep residual nets are foundations of our submissions to ILSVRC & COCO 2015 competitions, where we also won the 1st places on the tasks of ImageNet detection, ImageNet localization, COCO detection, and COCO segmentation.
#7 best model for Semantic Segmentation on Cityscapes val
This means that the super-resolution (SR) operation is performed in HR space.
A single neural network predicts bounding boxes and class probabilities directly from full images in one evaluation.
#2 best model for Real-Time Object Detection on PASCAL VOC 2007
In this work, we revisit the global average pooling layer proposed in , and shed light on how it explicitly enables the convolutional neural network to have remarkable localization ability despite being trained on image-level labels.
This paper studies a combination of generative Markov random field (MRF) models and discriminatively trained deep convolutional neural networks (dCNNs) for synthesizing 2D images.