Panoptic Scene Graph Generation
9 papers with code • 1 benchmarks • 1 datasets
PSG task abstracts the given image with a scene graph, where nodes are grounded by panoptic segmentation
Benchmarks
These leaderboards are used to track progress in Panoptic Scene Graph Generation
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Libraries
Use these libraries to find Panoptic Scene Graph Generation models and implementations
PSG Dataset
Most implemented papers
Neural Motifs: Scene Graph Parsing with Global Context
rowanz/neural-motifs
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CVPR 2018
We then introduce Stacked Motif Networks, a new architecture designed to capture higher order motifs in scene graphs that further improves over our strong baseline by an average 7. 1% relative gain.
Learning to Compose Dynamic Tree Structures for Visual Contexts
KaihuaTang/Scene-Graph-Benchmark.pytorch
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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.
Scene Graph Generation by Iterative Message Passing
microsoft/scene_graph_benchmark
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CVPR 2017
In this work, we explicitly model the objects and their relationships using scene graphs, a visually-grounded graphical structure of an image.
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.
Panoptic Scene Graph Generation
Existing research addresses scene graph generation (SGG) -- a critical technology for scene understanding in images -- from a detection perspective, i. e., objects are detected using bounding boxes followed by prediction of their pairwise relationships.
HiLo: Exploiting High Low Frequency Relations for Unbiased Panoptic Scene Graph Generation
Existing unbiased methods tackle the long-tail problem by data/loss rebalancing to favor low-frequency relations.
Pair then Relation: Pair-Net for Panoptic Scene Graph Generation
king159/pair-net
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Panoptic Scene Graph (PSG) is a challenging task in Scene Graph Generation (SGG) that aims to create a more comprehensive scene graph representation using panoptic segmentation instead of boxes.
Panoptic Scene Graph Generation with Semantics-Prototype Learning
lili0415/psg-biased-annotation
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To promise consistency and accuracy during the transfer process, we propose to measure the invariance of representations in each predicate class, and learn unbiased prototypes of predicates with different intensities.
VLPrompt: Vision-Language Prompting for Panoptic Scene Graph Generation
Panoptic Scene Graph Generation (PSG) aims at achieving a comprehensive image understanding by simultaneously segmenting objects and predicting relations among objects.
