Scene Graph Generation

46 papers with code • 3 benchmarks • 3 datasets

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

Greatest papers with code

Graph R-CNN for Scene Graph Generation

jwyang/graph-rcnn.pytorch ECCV 2018

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

KaihuaTang/Scene-Graph-Benchmark.pytorch CVPR 2020

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 +1

Learning to Compose Dynamic Tree Structures for Visual Contexts

KaihuaTang/Scene-Graph-Benchmark.pytorch CVPR 2019

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 +2

Scene Graph Generation from Objects, Phrases and Region Captions

yikang-li/MSDN ICCV 2017

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 +2

Image Scene Graph Generation (SGG) Benchmark

microsoft/scene_graph_benchmark 27 Jul 2021

There is a surge of interest in image scene graph generation (object, attribute and relationship detection) due to the need of building fine-grained image understanding models that go beyond object detection.

Graph Generation Object Detection +2

Graphical Contrastive Losses for Scene Graph Parsing

microsoft/scene_graph_benchmark CVPR 2019

The first, Entity Instance Confusion, occurs when the model confuses multiple instances of the same type of entity (e. g. multiple cups).

Scene Graph Generation Visual Relationship Detection

Scene Graph Generation by Iterative Message Passing

microsoft/scene_graph_benchmark CVPR 2017

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

Knowledge-Embedded Routing Network for Scene Graph Generation

yuweihao/KERN CVPR 2019

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