Scene Graph Generation
110 papers with code • 5 benchmarks • 7 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.
Benchmarks
These leaderboards are used to track progress in Scene Graph Generation
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Libraries
Use these libraries to find Scene Graph Generation models and implementations
MS COCO
Visual Genome
VRD
3DSSG
3RScan
PSG Dataset
4D-OR
Most implemented papers
RLIPv2: Fast Scaling of Relational Language-Image Pre-training
jacobyuan7/rlipv2
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ICCV 2023
In this paper, we propose RLIPv2, a fast converging model that enables the scaling of relational pre-training to large-scale pseudo-labelled scene graph data.
Panoptic Video Scene Graph Generation
jingkang50/openpvsg
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CVPR 2023
PVSG relates to the existing video scene graph generation (VidSGG) problem, which focuses on temporal interactions between humans and objects grounded with bounding boxes in videos.
Visual Graphs from Motion (VGfM): Scene understanding with object geometry reasoning
paulgay/VGfM
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Recent approaches on visual scene understanding attempt to build a scene graph -- a computational representation of objects and their pairwise relationships.
Relation Transformer Network
In this work, we propose a novel transformer formulation for scene graph generation and relation prediction.
Learning Visual Commonsense for Robust Scene Graph Generation
ZhecanJamesWang/GLAT_SGG
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ECCV 2020
Scene graph generation models understand the scene through object and predicate recognition, but are prone to mistakes due to the challenges of perception in the wild.
Learning and Reasoning with the Graph Structure Representation in Robotic Surgery
mobarakol/Surgical_SceneGraph_Generation
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Learning to infer graph representations and performing spatial reasoning in a complex surgical environment can play a vital role in surgical scene understanding in robotic surgery.
SceneGraphFusion: Incremental 3D Scene Graph Prediction from RGB-D Sequences
Scene graphs are a compact and explicit representation successfully used in a variety of 2D scene understanding tasks.
Fine-Grained Scene Graph Generation with Data Transfer
waxnkw/ietrans-sgg.pytorch
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Scene graph generation (SGG) is designed to extract (subject, predicate, object) triplets in images.
Scene Graph Generation from Objects, Phrases and Region Captions
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.
Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction
shikorab/SceneGraph
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NeurIPS 2018
Machine understanding of complex images is a key goal of artificial intelligence.
