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 561–570 of 712 papers

TitleStatusHype
Towards a Unified Transformer-based Framework for Scene Graph Generation and Human-object Interaction Detection—0
Towards Debiasing Frame Length Bias in Text-Video Retrieval via Causal Intervention—0
Towards Flexible Visual Relationship Segmentation—0
Towards Lifelong Scene Graph Generation with Knowledge-ware In-context Prompt Learning—0
Towards Localizing Structural Elements: Merging Geometrical Detection with Semantic Verification in RGB-D Data—0
Towards Open-vocabulary Scene Graph Generation with Prompt-based Finetuning—0
Towards Unbiased and Robust Spatio-Temporal Scene Graph Generation and Anticipation—0
Towards Unseen Triples: Effective Text-Image-joint Learning for Scene Graph Generation—0
Training-Free Guidance for Discrete Diffusion Models for Molecular Generation—0
Tri-modal Confluence with Temporal Dynamics for Scene Graph Generation in Operating Rooms—0
Show:102550
← PrevPage 57 of 72Next →

Benchmark Results

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