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 176–200 of 712 papers

TitleStatusHype
Expanding Scene Graph Boundaries: Fully Open-vocabulary Scene Graph Generation via Visual-Concept Alignment and RetentionCode1
ExplaGraphs: An Explanation Graph Generation Task for Structured Commonsense ReasoningCode1
Neural Graph Generator: Feature-Conditioned Graph Generation using Latent Diffusion ModelsCode1
Adaptive Graph Convolutional Recurrent Network for Traffic ForecastingCode1
Explanation Graph Generation via Pre-trained Language Models: An Empirical Study with Contrastive LearningCode1
CogTree: Cognition Tree Loss for Unbiased Scene Graph GenerationCode1
Exploiting Edge-Oriented Reasoning for 3D Point-based Scene Graph AnalysisCode1
GraphGUIDE: interpretable and controllable conditional graph generation with discrete Bernoulli diffusionCode1
OpenPSG: Open-set Panoptic Scene Graph Generation via Large Multimodal ModelsCode1
Combinatorial Complex Score-based Diffusion Modelling through Stochastic Differential EquationsCode1
ORacle: Large Vision-Language Models for Knowledge-Guided Holistic OR Domain ModelingCode1
Are scene graphs good enough to improve Image Captioning?Code1
Pair then Relation: Pair-Net for Panoptic Scene Graph GenerationCode1
Exploring the Individuality and Collectivity of Intents behind Interactions for Graph Collaborative FilteringCode1
Panoptic Video Scene Graph GenerationCode1
LANDMARK: Language-guided Representation Enhancement Framework for Scene Graph GenerationCode1
Expressive Scene Graph Generation Using Commonsense Knowledge Infusion for Visual Understanding and ReasoningCode1
Compositional Feature Augmentation for Unbiased Scene Graph GenerationCode1
Face Super-Resolution Using Stochastic Differential EquationsCode1
A Review and Efficient Implementation of Scene Graph Generation MetricsCode1
RAF: Holistic Compilation for Deep Learning Model TrainingCode1
Conditional Diffusion Based on Discrete Graph Structures for Molecular Graph GenerationCode1
PromptCAL: Contrastive Affinity Learning via Auxiliary Prompts for Generalized Novel Category DiscoveryCode1
Relationformer: A Unified Framework for Image-to-Graph GenerationCode1
Visual Graphs from Motion (VGfM): Scene understanding with object geometry reasoningCode1
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Benchmark Results

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