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LabelMe is a WEB-based image annotation tool and a Matlab toolbox that allows researchers to label images and share the annotations with the rest of the community. Copyright (C) 2007 MIT, Computer Science and Artificial Intelligence Laboratory. Antonio Torralba, Bryan Russell, William T. Freeman This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see <http://www.gnu.org/licenses/>.
semantic-segmentation-pytorch
Pytorch implementation for Semantic Segmentation/Scene Parsing on MIT ADE20K datasetplaces365
The Places365-CNNs for Scene Classificationgandissect
Pytorch-based tools for visualizing and understanding the neurons of a GAN. https://gandissect.csail.mit.edu/LabelMeAnnotationTool
Source code for the LabelMe annotation tool.GazeCapture
Eye Tracking for Everyonesceneparsing
Development kit for MIT Scene Parsing BenchmarkNetDissect
Network Dissection http://netdissect.csail.mit.edu for quantifying interpretability of deep CNNs.unifiedparsing
Codebase and pretrained models for ECCV'18 Unified Perceptual ParsingADE20K
ADE20K DatasetNetDissect-Lite
Light version of Network Dissection for Quantifying Interpretability of Networksplaceschallenge
The Toolkit for Places Challenge 2017miniplaces
MiniPlaces Challenge: an Educational Tool for Deep Learning in Computer VisionIBD
IBD: Interpretable Basis Decomposition for Visual ExplanationLabelMeMechanicalTurk
Toolbox for interfacing LabelMe with Mechanical TurkDetectMeApp
DetectMeMatlabToolbox
DetectMeServer
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