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The Stanford Natural Language Processing Group

nlp.stanford.edu · 1,153 words · saved by 1 readers

Scene Graphs are a graph-based semantic representation of image contents. They encode the objects in an image, their attributes and the relationships between objects. This system takes a single-sentence image description and parses it into a scene graph as described in the paper: The system requires Java 1.8+ to be installed, and it requires Stanford CoreNLP 3.6.0. We recommend running the system with at least 2gb of memory. (i.e., java -mx2g). The system is licensed under the GNU General Public License (v2 or later). Source is included. The package includes components for command-line invocation, and a Java API. To run the code, you need the CoreNLP jar and the CoreNLP models jar as well as the Scene Graph Parser jar in your classpath. You can either run the parser programmatically or in interactive mode through the command line. To parse sentences interactively, put all the jar files from the CoreNLP distribution and the Scene Graph Parser jar into one directory and then run the foll

The Stanford Natural Language Processing Group --> Software > Stanford Scene Graph Parser Stanford Scene Graph Parser | About | Download | Usage | Questions | About Scene Graphs are a graph-based semantic representation of image contents. They encode the objects in an image, their attributes and the relationships between objects. This system takes a single-sentence image description and parses it into a scene graph as described in the paper: Sebastian Schuster, Ranjay Krishna, Angel Chang, Li Fei-Fei, and Christopher D. Manning. 2015. Generating Semantically Precise Scene Graphs from Textual D

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