Browse SoTA > Computer Vision > Scene Parsing > Scene Graph Generation

Scene Graph Generation

14 papers with code · Computer Vision
Subtask of Scene Parsing

A scene graph is a structured representation of an image, where nodes in a scene graph correspond to object bounding boxes with their object categories, and edges correspond to their pairwise relationships between objects. The task of Scene Graph Generation is to generate a visually-grounded scene graph that most accurately correlates with an image.

Source: Scene Graph Generation by Iterative Message Passing

Benchmarks

Greatest papers with code

Graph R-CNN for Scene Graph Generation

ECCV 2018 jwyang/graph-rcnn.pytorch

We propose a novel scene graph generation model called Graph R-CNN, that is both effective and efficient at detecting objects and their relations in images.

GRAPH GENERATION SCENE GRAPH GENERATION

Unbiased Scene Graph Generation from Biased Training

CVPR 2020 KaihuaTang/Scene-Graph-Benchmark.pytorch

Today's scene graph generation (SGG) task is still far from practical, mainly due to the severe training bias, e. g., collapsing diverse "human walk on / sit on / lay on beach" into "human on beach".

CAUSAL INFERENCE GRAPH GENERATION SCENE GRAPH GENERATION

Learning to Compose Dynamic Tree Structures for Visual Contexts

CVPR 2019 KaihuaTang/Scene-Graph-Benchmark.pytorch

We propose to compose dynamic tree structures that place the objects in an image into a visual context, helping visual reasoning tasks such as scene graph generation and visual Q&A.

GRAPH GENERATION SCENE GRAPH GENERATION VISUAL QUESTION ANSWERING VISUAL REASONING

Scene Graph Generation from Objects, Phrases and Region Captions

ICCV 2017 yikang-li/MSDN

Object detection, scene graph generation and region captioning, which are three scene understanding tasks at different semantic levels, are tied together: scene graphs are generated on top of objects detected in an image with their pairwise relationship predicted, while region captioning gives a language description of the objects, their attributes, relations, and other context information.

GRAPH GENERATION OBJECT DETECTION SCENE GRAPH GENERATION SCENE UNDERSTANDING

Knowledge-Embedded Routing Network for Scene Graph Generation

CVPR 2019 yuweihao/KERN

More specifically, we show that the statistical correlations between objects appearing in images and their relationships, can be explicitly represented by a structured knowledge graph, and a routing mechanism is learned to propagate messages through the graph to explore their interactions.

GRAPH GENERATION SCENE GRAPH GENERATION

Scene Graph Generation by Iterative Message Passing

CVPR 2017 shikorab/SceneGraph

In this work, we explicitly model the objects and their relationships using scene graphs, a visually-grounded graphical structure of an image.

GRAPH GENERATION SCENE GRAPH GENERATION

The Limited Multi-Label Projection Layer

20 Jun 2019locuslab/lml

We propose the Limited Multi-Label (LML) projection layer as a new primitive operation for end-to-end learning systems.

GRAPH GENERATION SCENE GRAPH GENERATION

GPS-Net: Graph Property Sensing Network for Scene Graph Generation

CVPR 2020 taksau/GPS-Net

There are three key properties of scene graph that have been underexplored in recent works: namely, the edge direction information, the difference in priority between nodes, and the long-tailed distribution of relationships.

GRAPH GENERATION SCENE GRAPH GENERATION