Data to 14 Oct 2026

Neural Motifs: Scene Graph Parsing with Global Context

arXiv 1711.06640 ↗First posted 17 Nov 2017cs.CVcited by 414

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Cited by 25 in Multimodal LLMs / vision-language models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

We investigate the problem of producing structured graph representations of visual scenes. Our work analyzes the role of motifs: regularly appearing substructures in scene graphs. We present new quantitative insights on such repeated structures in the Visual Genome dataset. Our analysis shows that object labels are highly predictive of relation labels but not vice-versa. We also find that there are recurring patterns even in larger subgraphs: more than 50% of graphs contain motifs involving at least two relations. Our analysis motivates a new baseline: given object detections, predict the most frequent relation between object pairs with the given labels, as seen in the training set. This baseline improves on the previous state-of-the-art by an average of 3.6% relative improvement across evaluation settings. We then introduce Stacked Motif Networks, a new architecture designed to capture higher order motifs in scene graphs that further improves over our strong baseline by an average 7.1% relative gain. Our code is available at github.com/rowanz/neural-motifs.

Key facts. Cited by 414 papers in the map (data through 14 Oct 2026). First posted on arXiv 17 Nov 2017.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 77; 2022: 84; 2023: 94; 2024: 64; 2025: 52; 2026: 43.

414 papers.

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2022MERLOT Reserve: Neural Script Knowledge through Vision and Language and Soundcited by 184
2021CPT: Colorful Prompt Tuning for Pre-trained Vision-Language Modelscited by 183
2021Bipartite Graph Network with Adaptive Message Passing for Unbiased Scene Graph Generationcited by 137
2021A Comprehensive Survey of Scene Graphs: Generation and Applicationcited by 125
2022Panoptic Scene Graph Generationcited by 114
2021Energy-Based Learning for Scene Graph Generationcited by 104
2024SkySenseGPT: A Fine-Grained Instruction Tuning Dataset and Model for Remote Sensing Vision-Language Understandingcited by 104
2021SGTR: End-to-end Scene Graph Generation with Transformercited by 103
2021Spatial-Temporal Transformer for Dynamic Scene Graph Generationcited by 96
2022RelTR: Relation Transformer for Scene Graph Generationcited by 96
2021Semantic Communications: Principles and Challengescited by 91
2024The All-Seeing Project V2: Towards General Relation Comprehension of the Open Worldcited by 90

38 more

2021TransRefer3D: Entity-and-Relation Aware Transformer for Fine-Grained 3D Visual Groundingcited by 86
2021Graph-to-3D: End-to-End Generation and Manipulation of 3D Scenes Using Scene Graphscited by 84
2022Multi-Modal Knowledge Graph Construction and Application: A Surveycited by 74
2022Scene Graph Generation: A Comprehensive Surveycited by 73
2021Recovering the Unbiased Scene Graphs from the Biased Onescited by 71
2022Stacked Hybrid-Attention and Group Collaborative Learning for Unbiased Scene Graph Generationcited by 67
2022Relationformer: A Unified Framework for Image-to-Graph Generationcited by 67
2021Learning of Visual Relations: The Devil is in the Tailscited by 65
2021Learning to Generate Scene Graph from Natural Language Supervisioncited by 64
2022The Devil is in the Labels: Noisy Label Correction for Robust Scene Graph Generationcited by 60
2021Fully Convolutional Scene Graph Generationcited by 57
2022Fine-Grained Scene Graph Generation with Data Transfercited by 57
2021Semantics for Robotic Mapping, Perception and Interaction: A Surveycited by 56
2022A Survey on Graph Neural Networks and Graph Transformers in Computer Vision: A Task-Oriented Perspectivecited by 56
2022Towards Open-vocabulary Scene Graph Generation with Prompt-based Finetuningcited by 54
2021Target Adaptive Context Aggregation for Video Scene Graph Generationcited by 52
2021From General to Specific: Informative Scene Graph Generation via Balance Adjustmentcited by 51
2023FACTUAL: A Benchmark for Faithful and Consistent Textual Scene Graph Parsingcited by 50
2021Exploiting Edge-Oriented Reasoning for 3D Point-based Scene Graph Analysiscited by 49
2024EGTR: Extracting Graph from Transformer for Scene Graph Generationcited by 47
2023Panoptic Video Scene Graph Generationcited by 46
2023RLIPv2: Fast Scaling of Relational Language-Image Pre-trainingcited by 45
2021Structured Sparse R-CNN for Direct Scene Graph Generationcited by 44
2022Deep Learning Approaches on Image Captioning: A Reviewcited by 43
2023VL-SAT: Visual-Linguistic Semantics Assisted Training for 3D Semantic Scene Graph Prediction in Point Cloudcited by 43
2024From Pixels to Graphs: Open-Vocabulary Scene Graph Generation with Vision-Language Modelscited by 43
2021Spatio-Temporal Dynamic Inference Network for Group Activity Recognitioncited by 42
2023Panoptic Scene Graph Generation with Semantics-Prototype Learningcited by 42
2023SceneGenie: Scene Graph Guided Diffusion Models for Image Synthesiscited by 41
2022Continuous Scene Representations for Embodied AIcited by 39
2023Unbiased Scene Graph Generation in Videoscited by 39
2023Incorporating Structured Representations into Pretrained Vision & Language Models Using Scene Graphscited by 39
2022Latent Graph Representations for Critical View of Safety Assessmentcited by 37
2023Prototype-based Embedding Network for Scene Graph Generationcited by 37
2023Structure-CLIP: Towards Scene Graph Knowledge to Enhance Multi-modal Structured Representationscited by 37
2021Probabilistic Modeling of Semantic Ambiguity for Scene Graph Generationcited by 35
2023Visually-Prompted Language Model for Fine-Grained Scene Graph Generation in an Open Worldcited by 35
2022Contrastive Language-Image Pre-Training with Knowledge Graphscited by 34

50 most cited of 414 All 414 (JSON)