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 5175 of 82 papers

TitleStatusHype
Contextual Translation Embedding for Visual Relationship Detection and Scene Graph Generation0
On Exploring Undetermined Relationships for Visual Relationship Detection0
Improving Visual Relation Detection using Depth MapsCode0
Visual Relationship Detection with Language prior and SoftmaxCode0
Target-Tailored Source-Transformation for Scene Graph Generation0
Scene Graph Generation with External Knowledge and Image Reconstruction0
Optimising the Input Image to Improve Visual Relationship Detection0
On Class Imbalance and Background Filtering in Visual Relationship Detection0
Visual Semantic Information Pursuit: A Survey0
Graphical Contrastive Losses for Scene Graph ParsingCode1
Deeply Supervised Multimodal Attentional Translation Embeddings for Visual Relationship DetectionCode0
BLOCK: Bilinear Superdiagonal Fusion for Visual Question Answering and Visual Relationship DetectionCode0
An Interpretable Model for Scene Graph Generation0
The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scaleCode0
Introduction to the 1st Place Winning Model of OpenImages Relationship Detection Challenge0
A Problem Reduction Approach for Visual Relationships Detection0
Context-Dependent Diffusion Network for Visual Relationship Detection0
Improving Visual Relationship Detection using Semantic Modeling of Scene Descriptions0
Improving Information Extraction from Images with Learned Semantic Models0
Factorizable Net: An Efficient Subgraph-based Framework for Scene Graph GenerationCode0
Tensorize, Factorize and Regularize: Robust Visual Relationship Learning0
Visual Relationship Detection Based on Guided Proposals and Semantic Knowledge Distillation0
Visual relationship detection with deep structural rankingCode0
Natural Language Guided Visual Relationship Detection0
Attend and Interact: Higher-Order Object Interactions for Video Understanding0
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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