Properties of dilated convolution are discussed in our ICLR 2016 conference paper. This repository contains the network definitions and the trained models. You can use this code together with vanilla Caffe to segment images using the pre-trained models. If you want to train the models yourself,…
This project is a modular PyTorch framework for training and evaluating object detection and instance segmentation models. It serves as a computer vision research tool and a deep learning inference engine designed to identify object locations, classes, and pixel-level masks within images. The framework implements a two-stage inference pipeline that utilizes region proposal networks and a symmetric mask-head architecture. It provides specialized capabilities for instance segmentation, object bounding box detection, and human pose estimation via anatomical keypoint detection. The system includ
Implementation of various Deep Image Segmentation models in keras.
DeconvNet : Learning Deconvolution Network for Semantic Segmentation
hyeonwoonoh/deconvnet 的主要功能包括：Computer Vision Models, Segmentation Architectures, Semantic Segmentation。
hyeonwoonoh/deconvnet 的开源替代品包括： hszhao/pspnet — by Hengshuang Zhao, Jianping Shi, Xiaojuan Qi, Xiaogang Wang, Jiaya Jia, details are in project page. guosheng/refinenet. facebookresearch/maskrcnn-benchmark — This project is a modular PyTorch framework for training and evaluating object detection and instance segmentation… divamgupta/image-segmentation-keras — Implementation of various Deep Image Segmentation models in keras. fyu/dilation — Properties of dilated convolution are discussed in our ICLR 2016 conference paper. This repository contains the… isht7/pytorch-deeplab-resnet.