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automatic-image-co-segmentation-using-geometric-mean-saliency-top-10-paper-award-icip-14-

An image co-segmentation algorithm that was presented in ICIP'14. It has been recipient of Top 10% paper award as well.

caffe

Caffe: a fast open framework for deep learning.

cf-caffe

Caffe designed for Deep Context Features

cosaliency_tip2013

The codes for "Cluster-based Co-saliency Detection" in TIP 2013.

dalcim

Testing multi-class cosegmentation http://www.di.ens.fr/~joulin/index?page=coseg

faster_rcnn

Faster R-CNN

gco-v3.0

Multi-label optimization library by Olga Veksler and Andrew Delong

group-saliency-propagation-for-large-scale-and-quick-image-co-segmentation

A co-segmentation method that appears in ICIP'15

matlab-schemer

Apply and save color schemes in MATLAB with ease.

models

Models and examples built with TensorFlow

papers-note

picanet

pwc

Papers with code. Sorted by stars. Updated weekly.

radf

AAAI 2018 (Spotlight)

saliency

Code for http://saliency.mit.edu/

saliency-co-fusion

Matlab Implementation of "Image Co-segmentation via Saliency Co-fusion", IEEE Trans. Multimedia 2016 paper

saliency_metrics

semantic-segmentation-suite

Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!

stanford-tensorflow-tutorials

This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.

ucf-sports-annotations

UCF Sports annotations: This repository provides human bounding box annotations of UCF Sports dataset and a function to read these annotations.

video-object-segmentation

Joint Motion Boundary Detection and CNN-based Feature Visualization for Video Object Segmentation Version 1 ---------------------------------------------------------------------------------------------------------------------------------- The source code is prepared for video object segmentation [I,II]. The code can be run on the videos which their objects have been already trained in VGG-16. However, it can be applied to any videos, provided that a new CNN is trained on a dataset that includes its common object class. Using the code: 1- Please download, install and compile Matconvnet from (http://www.vlfeat.org/matconvnet/). To speed up code execution, please compile the software in GPU support version. 2- Please download 'imagenet-vgg-verydeep-16.mat' [1] from (http://www.vlfeat.org/matconvnet/pretrained/), and load the model. [1] Simonyan K, Zisserman A (2014) Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:14091556. 3- For oversegmentation, gPb-UCM code is used [2,3]. Please download and install mcg-2.0 code from (https://www2.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/resources.html) [2]P. Arbelaez, J. Pont-Tuset, J. T. Barron, F. Marques, J. Malik, Multiscale combinatorial grouping, in: Computer Vision and Pattern Recognition (CVPR), Conference on, IEEE, 2014, pp. 328-335. [3] P. Arbelaez, M. Maire, C. Fowlkes, J. Malik, Contour detection and hierarchical image segmentation, Pattern Analysis and Machine Intelligence, IEEE transactions on 33 (2011) 898-916. 4- Please download and compile Matlab wrappers from (http://calvin.inf.ed.ac.uk/software/fast-video-segmentation/) to find motion boundary detection [4]. [4] Papazoglou A, Ferrari V (2013) Fast object segmentation in unconstrained video. In: Computer Vision (ICCV) International Conference, IEEE, pp 1777–1784. 5- run main_demo.m Please note that the code is the first version. In this version, - some functions are simpler than original ones. - Inspired by [5], we use spline regression to learn the local energy. Thus, some results may are different from what is reported on the paper [II]. [5] X. Dong, J. Shen, L. Shao, M.-H. Yang, Interactive cosegmentation using global and local energy optimization, Image Processing, IEEE Transactions on 24 (2015) 3966{3977. For further information, please do not hesitate to contact [email protected] If you use this software for academic research, please cite the following publication: [I] Kamranian Z, Tombari F, Nilchi ARN, Monadjemi A, Navab N (2018) Co-segmentation via visualization. Journal of Visual Communication and Image Representation 55:201–214. [II] Kamranian Z, Nilchi ARN, Sadeghian H, Tombari F, Navab N (2019)Joint Motion Boundary Detection and CNN-based Feature Visualization for Video Object Segmentation. Neural Computing with Applications.

watershed

A Python implementation of the watershed image segmentation algorithm

watershed-1

Python implementation of a varient of Watershed clustering

zhaomin.github.com