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算力平台

Scene Graph Generation On Visual Genome

评估指标

Recall@100
Recall@20
Recall@50

评测结果

各个模型在此基准测试上的表现结果

Paper Title
SpeaQ (without reweighting)36.0-32.9Groupwise Query Specialization and Quality-Aware Multi-Assignment for Transformer-based Visual Relationship Detection
SpeaQ (with reweighting)35.5-32.1Groupwise Query Specialization and Quality-Aware Multi-Assignment for Transformer-based Visual Relationship Detection
Causal-TDE--31.93Unbiased Scene Graph Generation from Biased Training
SG-EBM--31.74Energy-Based Learning for Scene Graph Generation
GPS-Net--28.9GPS-Net: Graph Property Sensing Network for Scene Graph Generation
LOGIN31.422.228.2Tackling the Challenges in Scene Graph Generation with Local-to-Global Interactions
VCTree--27.9Learning to Compose Dynamic Tree Structures for Visual Contexts
NODIS-21.627.7NODIS: Neural Ordinary Differential Scene Understanding
KERN--27.1Knowledge-Embedded Routing Network for Scene Graph Generation
DLFE--25.4Recovering the Unbiased Scene Graphs from the Biased Ones
IETrans27.2-23.5Fine-Grained Scene Graph Generation with Data Transfer
ADTrans--23.0Panoptic Scene Graph Generation with Semantics-Prototype Learning
Graph-RCNN--11.4Graph R-CNN for Scene Graph Generation
MSDN--10.72Scene Graph Generation from Objects, Phrases and Region Captions
ExpressiveSGG---Expressive Scene Graph Generation Using Commonsense Knowledge Infusion for Visual Understanding and Reasoning
C-bias---Biasing Like Human: A Cognitive Bias Framework for Scene Graph Generation
CogTree---CogTree: Cognition Tree Loss for Unbiased Scene Graph Generation
KnowZRel---KnowZRel: Common Sense Knowledge-based Zero-Shot Relationship Retrieval for Generalised Scene Graph Generation
NeuSyRE---NeuSyRE: Neuro-Symbolic Visual Understanding and Reasoning Framework based on Scene Graph Enrichment
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Scene Graph Generation On Visual Genome | SOTA | HyperAI超神经