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 231–240 of 712 papers

TitleStatusHype
Swap-based Deep Reinforcement Learning for Facility Location Problems in Networks—0
Indoor and Outdoor 3D Scene Graph Generation via Language-Enabled Spatial Ontologies—0
Collect and Connect Data Leaves to Feature Concepts: Interactive Graph Generation Toward Well-being—0
Efficient and Scalable Graph Generation through Iterative Local ExpansionCode1
GPT4SGG: Synthesizing Scene Graphs from Holistic and Region-specific NarrativesCode0
HIG: Hierarchical Interlacement Graph Approach to Scene Graph Generation in Video Understanding—0
A Simple and Scalable Representation for Graph GenerationCode1
HAtt-Flow: Hierarchical Attention-Flow Mechanism for Group Activity Scene Graph Generation in Videos—0
Panoptic Video Scene Graph GenerationCode1
VLPrompt: Vision-Language Prompting for Panoptic Scene Graph GenerationCode1
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Benchmark Results

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