SOTAVerified

Graph Generation

Graph Generation is an important research area with significant applications in drug and material designs.

Source: Graph Deconvolutional Generation

Papers

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Showing 281–290 of 712 papers

TitleStatusHype
RLIPv2: Fast Scaling of Relational Language-Image Pre-trainingCode1
Vision Relation Transformer for Unbiased Scene Graph GenerationCode1
Compositional Feature Augmentation for Unbiased Scene Graph GenerationCode1
3D Scene Graph Prediction on Point Clouds Using Knowledge Graphs—0
Informative Scene Graph Generation via Debiasing—0
Local-Global Information Interaction Debiasing for Dynamic Scene Graph Generation—0
Generalized Unbiased Scene Graph Generation—0
Environment-Invariant Curriculum Relation Learning for Fine-Grained Scene Graph GenerationCode0
Improving Scene Graph Generation with Superpixel-Based Interaction Learning—0
Text2KGBench: A Benchmark for Ontology-Driven Knowledge Graph Generation from TextCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1RNNStreetMover0.03—Unverified
2GraphRNNStreetMover0.02—Unverified
3GGT without CAStreetMover0.02—Unverified
4GGTStreetMover0.02—Unverified