SOTAVerified

Relational Reasoning

The goal of Relational Reasoning is to figure out the relationships among different entities, such as image pixels, words or sentences, human skeletons or interactive moving agents.

Source: Social-WaGDAT: Interaction-aware Trajectory Prediction via Wasserstein Graph Double-Attention Network

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 211–220 of 483 papers

TitleStatusHype
Learning Symbolic Operators for Task and Motion PlanningCode1
A Universal Model for Cross Modality Mapping by Relational Reasoning—0
Spatio-Temporal Graph Dual-Attention Network for Multi-Agent Prediction and Tracking—0
A Statistical Relational Approach to Learning Distance-based GCNs—0
Improving Scene Graph Classification by Exploiting Knowledge from Texts—0
Cross Chest Graph for Disease Diagnosis with Structural Relational Reasoning—0
Context Aware Group Activity Recognition—0
HAIR: Hierarchical Visual-Semantic Relational Reasoning for Video Question Answering—0
Relational Learning with Variational Bayes—0
GraphLog: A Benchmark for Measuring Logical Generalization in Graph Neural NetworksCode1
Show:102550
← PrevPage 22 of 49Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified