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 261–270 of 483 papers

TitleStatusHype
Relational Neural Markov Random Fields—0
Relational Reasoning Network (RRN) for Anatomical Landmarking—0
Behavior-Inspired Neural Networks for Relational Inference—0
Relational Reasoning Over Spatial-Temporal Graphs for Video Summarization—0
Relational Reasoning using Prior Knowledge for Visual Captioning—0
Relational Reasoning via Set Transformers: Provable Efficiency and Applications to MARL—0
Relational Similarity Machines—0
Relation Matters: Foreground-aware Graph-based Relational Reasoning for Domain Adaptive Object Detection—0
RelEx: A Model-Agnostic Relational Model Explainer—0
RelNet: End-to-End Modeling of Entities & Relations—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified