SOTAVerified

Visual Relationship Detection

Visual relationship detection (VRD) is one newly developed computer vision task aiming to recognize relations or interactions between objects in an image. It is a further learning task after object recognition and is essential for fully understanding images, even the visual world.

Papers

Showing 2650 of 82 papers

TitleStatusHype
Scene Graph Generation with External Knowledge and Image Reconstruction0
A Comprehensive Survey of Scene Graphs: Generation and Application0
Scene-Graph ViT: End-to-End Open-Vocabulary Visual Relationship Detection0
VReBERT: A Simple and Flexible Transformer for Visual Relationship Detection0
Tensorize, Factorize and Regularize: Robust Visual Relationship Learning0
An Interpretable Model for Scene Graph Generation0
A Probabilistic Graphical Model Based on Neural-Symbolic Reasoning for Visual Relationship Detection0
A Problem Reduction Approach for Visual Relationships Detection0
Attend and Interact: Higher-Order Object Interactions for Video Understanding0
BGT-Net: Bidirectional GRU Transformer Network for Scene Graph Generation0
Bounding-box Channels for Visual Relationship Detection0
Care about you: towards large-scale human-centric visual relationship detection0
Context-Dependent Diffusion Network for Visual Relationship Detection0
CPARR: Category-based Proposal Analysis for Referring Relationships0
Deep Adaptive Semantic Logic (DASL): Compiling Declarative Knowledge into Deep Neural Networks0
Deep Contextual Attention for Human-Object Interaction Detection0
Target-Tailored Source-Transformation for Scene Graph Generation0
Fixed-size Objects Encoding for Visual Relationship Detection0
ViP-CNN: Visual Phrase Guided Convolutional Neural Network0
Visual Relationship Detection Using Part-and-Sum Transformers with Composite Queries0
Hierarchical Graph Attention Network for Visual Relationship Detection0
Image Semantic Relation Generation0
Improving Information Extraction from Images with Learned Semantic Models0
Improving Visual Relationship Detection using Semantic Modeling of Scene Descriptions0
Introduction to the 1st Place Winning Model of OpenImages Relationship Detection Challenge0
Show:102550
← PrevPage 2 of 4Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Yu et. al [[Yu et al.2017a]]R@10031.89Unverified
2vrd-dsrR@10023.29Unverified
3BLOCKR@10020.96Unverified
4Dai et. al [[Dai, Zhang, and Lin2017]]R@10020.88Unverified
5Liang et. al [[Liang, Lee, and Xing2017]]R@10020.79Unverified
6Peyre et. al [[Peyre et al.2017]]R@10017.1Unverified
7Zhang et. al [[Hanwang Zhang2017]]R@10015.2Unverified
8Lu et. al [[Lu et al.2016]]R@10014.7Unverified
#ModelMetricClaimedVerifiedStatus
1Yu et. al [[Yu et al.2017a]]R@10029.43Unverified
2BLOCKR@10028.96Unverified
3Dai et. al [[Dai, Zhang, and Lin2017]]R@10023.45Unverified
4Liang et. al [[Liang, Lee, and Xing2017]]R@10022.6Unverified
5Zhang et. al [[Hanwang Zhang2017]]R@10022.42Unverified
6Peyre et. al [[Peyre et al.2017]]R@10019.5Unverified
7Lu et. al [[Lu et al.2016]]R@10017.03Unverified
#ModelMetricClaimedVerifiedStatus
1Yu et. al [[Yu et al.2017a]]R@10094.65Unverified
2vrd-dsrR@10093.18Unverified
3BLOCKR@10092.58Unverified
4Dai et. al [[Dai, Zhang, and Lin2017]]R@10081.9Unverified
5Peyre et. al [[Peyre et al.2017]]R@10052.6Unverified
6Lu et. al [[Lu et al.2016]]R@10047.87Unverified
7Zhang et. al [[Hanwang Zhang2017]]R@10044.76Unverified
#ModelMetricClaimedVerifiedStatus
1PEVLR@10066.3Unverified
#ModelMetricClaimedVerifiedStatus
1Ours - vR@50 k=115Unverified