SOTAVerified

Graph Generation

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

Source: Graph Deconvolutional Generation

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 471–480 of 712 papers

TitleStatusHype
Visual Traffic Knowledge Graph Generation from Scene Images—0
Skew Class-balanced Re-weighting for Unbiased Scene Graph GenerationCode0
Fast Contextual Scene Graph Generation With Unbiased Context Augmentation—0
IS-GGT: Iterative Scene Graph Generation With Generative Transformers—0
RealGraph: A Multiview Dataset for 4D Real-world Context Graph Generation—0
Peer Learning for Unbiased Scene Graph Generation—0
EDoG: Adversarial Edge Detection For Graph Neural Networks—0
SrTR: Self-reasoning Transformer with Visual-linguistic Knowledge for Scene Graph Generation—0
Molecular Graph Generation by Decomposition and Reassembling—0
Iterative Scene Graph Generation with Generative Transformers—0
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Benchmark Results

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