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
Unified Visual Relationship Detection with Vision and Language ModelsCode0
Image Semantic Relation Generation0
Learning Structured Representations of Visual Scenes0
VReBERT: A Simple and Flexible Transformer for Visual Relationship Detection0
Scene Graph Generation: A Comprehensive Survey0
A Probabilistic Graphical Model Based on Neural-Symbolic Reasoning for Visual Relationship Detection0
Representing Prior Knowledge Using Randomly, Weighted Feature Networks for Visual Relationship DetectionCode0
BGT-Net: Bidirectional GRU Transformer Network for Scene Graph Generation0
Image Scene Graph Generation (SGG) BenchmarkCode0
Visual Relationship Detection Using Part-and-Sum Transformers with Composite Queries0
A Comprehensive Survey of Scene Graphs: Generation and Application0
Towards Overcoming False Positives in Visual Relationship Detection0
Visualization of Contributions to Open-Source ProjectsCode0
Constructing a Visual Relationship Authenticity DatasetCode0
Bounding-box Channels for Visual Relationship Detection0
Hierarchical Graph Attention Network for Visual Relationship Detection0
Fixed-size Objects Encoding for Visual Relationship Detection0
Visual Relationship Detection using Scene Graphs: A Survey0
CPARR: Category-based Proposal Analysis for Referring Relationships0
ReLaText: Exploiting Visual Relationships for Arbitrary-Shaped Scene Text Detection with Graph Convolutional Networks0
AVR: Attention based Salient Visual Relationship DetectionCode0
Deep Adaptive Semantic Logic (DASL): Compiling Declarative Knowledge into Deep Neural Networks0
Visual Relationship Detection with Low Rank Non-Negative Tensor Decomposition0
Visual Relationship Detection with Relative Location MiningCode0
Leveraging Auxiliary Text for Deep Recognition of Unseen Visual Relationships0
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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