Zheng, Z.X.[Zhen-Xing],
Li, Z.D.[Zhen-Dong],
An, G.Y.[Gao-Yun],
Feng, S.H.[Song-He],
Subgraph and object context-masked network for scene graph generation,
IET-CV(14), No. 7, October 2020, pp. 546-553.
DOI Link
2010
BibRef
Xu, N.[Ning],
Liu, A.A.[An-An],
Wong, Y.K.[Yong-Kang],
Nie, W.Z.[Wei-Zhi],
Su, Y.T.[Yu-Ting],
Kankanhalli, M.[Mohan],
Scene Graph Inference via Multi-Scale Context Modeling,
CirSysVideo(31), No. 3, March 2021, pp. 1031-1041.
IEEE DOI
2103
Visualization, Context modeling, Proposals, Feature extraction,
Semantics, Head, Safety, Scene graph, context-fused inference,
multi-scale context
BibRef
Hung, Z.S.[Zih-Siou],
Mallya, A.[Arun],
Lazebnik, S.[Svetlana],
Contextual Translation Embedding for Visual Relationship Detection
and Scene Graph Generation,
PAMI(43), No. 11, November 2021, pp. 3820-3832.
IEEE DOI
2110
Visualization, Feature extraction, Task analysis, Training,
Semantics, Bicycles, Image edge detection,
scene understanding
BibRef
Zhou, H.[Hao],
Yang, Y.Z.[Ya-Zhou],
Luo, T.J.[Ting-Jin],
Zhang, J.[Jun],
Li, S.H.[Shuo-Hao],
A unified deep sparse graph attention network for scene graph
generation,
PR(123), 2022, pp. 108367.
Elsevier DOI
2112
Scene graph generation, Statistical co-occurrence knowledge,
Relationship measurement network, Graph attention network, Sparse graph
BibRef
Lin, B.Q.[Bing-Qian],
Zhu, Y.[Yi],
Liang, X.D.[Xiao-Dan],
Atom correlation based graph propagation for scene graph generation,
PR(122), 2022, pp. 108300.
Elsevier DOI
2112
Scene graph generation, Long-tailed distribution,
Knowledge graph, Atom correlation, Category space
BibRef
Li, P.[Ping],
Yu, Z.[Zhou],
Zhan, Y.B.[Yi-Bing],
Deep relational self-Attention networks for scene graph generation,
PRL(153), 2022, pp. 200-206.
Elsevier DOI
2201
Scene graph generation, Image understanding, Deep neural networks
BibRef
Wald, J.[Johanna],
Navab, N.[Nassir],
Tombari, F.[Federico],
Learning 3D Semantic Scene Graphs with Instance Embeddings,
IJCV(130), No. 3, March 2022, pp. 630-651.
Springer DOI
2203
BibRef
Garg, S.[Sarthak],
Dhamo, H.[Helisa],
Farshad, A.[Azade],
Musatian, S.[Sabrina],
Navab, N.[Nassir],
Tombari, F.[Federico],
Unconditional Scene Graph Generation,
ICCV21(16342-16351)
IEEE DOI
2203
Measurement, Image synthesis, Computational modeling,
Image edge detection, Semantics, Directed graphs, Neural generative models
BibRef
Tao, L.T.[Lei-Tian],
Mi, L.[Li],
Li, N.N.[Nan-Nan],
Cheng, X.H.[Xian-Hang],
Hu, Y.[Yaosi],
Chen, Z.Z.[Zhen-Zhong],
Predicate Correlation Learning for Scene Graph Generation,
IP(31), 2022, pp. 4173-4185.
IEEE DOI
2206
Correlation, Tail, Semantics, Head, Visualization,
Phase change materials, Optimization, Image understanding,
semantic overlap
BibRef
Luo, J.[Jie],
Zhao, J.[Jia],
Wen, B.[Bin],
Zhang, Y.H.[Yu-Hang],
Explaining the semantics capturing capability of scene graph
generation models,
PR(110), 2021, pp. 107427.
Elsevier DOI
2011
Explanation, Metrics, Semantic property, Scene graph generation,
Deep neural network
BibRef
Guo, Y.Y.[Yu-Yu],
Gao, L.L.[Lian-Li],
Song, J.K.[Jing-Kuan],
Wang, P.[Peng],
Sebe, N.[Nicu],
Shen, H.T.[Heng Tao],
Li, X.L.[Xue-Long],
Relation Regularized Scene Graph Generation,
Cyber(52), No. 7, July 2022, pp. 5961-5972.
IEEE DOI
2207
Visualization, Feature extraction, Task analysis, Semantics,
Detectors, Proposals, Convolution, visual relationship
BibRef
Zhao, B.[Bowen],
Mao, Z.D.[Zhen-Dong],
Fang, S.C.[Shan-Cheng],
Zang, W.Y.[Wen-Yu],
Zhang, Y.D.[Yong-Dong],
Semantically Similarity-Wise Dual-Branch Network for Scene Graph
Generation,
CirSysVideo(32), No. 7, July 2022, pp. 4573-4583.
IEEE DOI
2207
Visualization, Semantics, Feature extraction, Data mining, Encoding,
Message passing, Training, Scene graph generation, message propagating
BibRef
Lin, Z.Y.[Zhi-Yuan],
Zhu, F.[Feng],
Wang, Q.[Qun],
Kong, Y.Z.[Yan-Zi],
Wang, J.Y.[Jian-Yu],
Huang, L.[Liang],
Hao, Y.M.[Ying-Ming],
RSSGG_CS: Remote Sensing Image Scene Graph Generation by Fusing
Contextual Information and Statistical Knowledge,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Chang, X.J.[Xiao-Jun],
Ren, P.Z.[Peng-Zhen],
Xu, P.F.[Peng-Fei],
Li, Z.H.[Zhi-Hui],
Chen, X.J.[Xiao-Jiang],
Hauptmann, A.[Alex],
A Comprehensive Survey of Scene Graphs: Generation and Application,
PAMI(45), No. 1, January 2023, pp. 1-26.
IEEE DOI
2212
Survey, Graphs. Visualization, Task analysis, Feature extraction,
Image recognition, Cognition, Training, Systematics, Scene graph,
visual relationship recognition
BibRef
Han, X.J.[Xian-Jing],
Dong, X.N.[Xing-Ning],
Song, X.M.[Xue-Meng],
Gan, T.[Tian],
Zhan, Y.B.[Yi-Bing],
Yan, Y.[Yan],
Nie, L.Q.[Li-Qiang],
Divide-and-Conquer Predictor for Unbiased Scene Graph Generation,
CirSysVideo(32), No. 12, December 2022, pp. 8611-8622.
IEEE DOI
2212
Correlation, Image analysis, Task analysis,
Business process re-engineering, Predictive models,
Bayesian personalized ranking
BibRef
He, T.[Tao],
Gao, L.[Lianli],
Song, J.[Jingkuan],
Li, Y.F.[Yuan-Fang],
State-Aware Compositional Learning Toward Unbiased Training for Scene
Graph Generation,
IP(32), 2023, pp. 43-56.
IEEE DOI
2301
Visualization, Training, Task analysis, Predictive models, Dogs,
Standards, Genomics, Scene graph generation, feature decomposition,
data augmentation
BibRef
Wang, Y.[Yu],
Hu, L.[Liang],
Gao, W.[Wanfu],
Cao, X.F.[Xiao-Feng],
Chang, Y.[Yi],
AdaNS: Adaptive negative sampling for unsupervised graph
representation learning,
PR(136), 2023, pp. 109266.
Elsevier DOI
2301
Graph representation learning, Negative sampling, Noise contrastive estimation
BibRef
Zhou, H.[Hao],
Zhang, J.[Jun],
Luo, T.[Tingjin],
Yang, Y.Z.[Ya-Zhou],
Lei, J.[Jun],
Debiased Scene Graph Generation for Dual Imbalance Learning,
PAMI(45), No. 4, April 2023, pp. 4274-4288.
IEEE DOI
2303
Tail, Correlation, Training, Resistance, Visualization, Task analysis,
Semantics, Scene graph generation, dual imbalance learning,
context bias
BibRef
Li, X.[Xuewei],
Wu, T.[Tao],
Zheng, G.[Guangcong],
Yu, Y.L.[Yun-Long],
Li, X.[Xi],
Uncertainty-Aware Scene Graph Generation,
PRL(167), 2023, pp. 30-37.
Elsevier DOI
2303
Scene graph generation, Uncertainty analysis,
Bayesian classifier reparameterization
BibRef
Feng, S.Y.[Sheng-Yu],
Mostafa, H.[Hesham],
Nassar, M.[Marcel],
Majumdar, S.[Somdeb],
Tripathi, S.[Subarna],
Exploiting Long-Term Dependencies for Generating Dynamic Scene Graphs,
WACV23(5119-5128)
IEEE DOI
2302
Fluctuations, Source coding, Genomics, Benchmark testing,
Transformers, Bioinformatics, visual reasoning
BibRef
Adaimi, G.[George],
Mizrahi, D.[David],
Alahi, A.[Alexandre],
Composite Relationship Fields with Transformers for Scene Graph
Generation,
WACV23(52-64)
IEEE DOI
2302
Visualization, Image recognition, Image synthesis, Semantics,
Genomics, Transformers, Real-time systems,
Commercial/retail
BibRef
Hasegawa, S.[So],
Hiromoto, M.[Masayuki],
Nakagawa, A.[Akira],
Umeda, Y.[Yuhei],
Improving Predicate Representation in Scene Graph Generation by
Self-Supervised Learning,
WACV23(2739-2748)
IEEE DOI
2302
Visualization, Genomics, Self-supervised learning, Task analysis,
Bioinformatics,
and un-supervised learning)
BibRef
Trivedy, V.[Vivek],
Latecki, L.J.[Longin Jan],
CNN2Graph: Building Graphs for Image Classification,
WACV23(1-11)
IEEE DOI
2302
Training, Representation learning, Costs, Transformers,
Inference algorithms, Graph neural networks, Data models,
and un-supervised learning)
BibRef
Wang, J.J.[Jian-Jia],
Zhao, X.[Xin],
Wu, C.[Chong],
Hancock, E.R.[Edwin R.],
Inferring Edges from Weights in the Debye Model,
ICPR22(3845-3850)
IEEE DOI
2212
Gamma distribution, Solid modeling, Temperature distribution,
Thermodynamics, Temperature dependence, Solids, Probability distribution
BibRef
Li, J.[Jingci],
Lu, G.Q.[Guang-Quan],
Wu, Z.T.[Zheng-Tian],
Multi-View Graph Autoencoder for Unsupervised Graph Representation
Learning,
ICPR22(2213-2218)
IEEE DOI
2212
Representation learning, Training, Social networking (online),
Network topology, Aggregates, Topology
BibRef
Seymour, Z.[Zachary],
Mithun, N.C.[Niluthpol Chowdhury],
Chiu, H.P.[Han-Pang],
Samarasekera, S.[Supun],
Kumar, R.[Rakesh],
GraphMapper: Efficient Visual Navigation by Scene Graph Generation,
ICPR22(4146-4153)
IEEE DOI
2212
Visualization,
Simultaneous localization and mapping, Navigation, Autonomous agents
BibRef
Zhang, Y.Z.[Yi-Zhou],
Zheng, Z.H.[Zhao-Heng],
Nevatia, R.[Ram],
Liu, Y.[Yan],
Improving Weakly Supervised Scene Graph Parsing through Object
Grounding,
ICPR22(4058-4064)
IEEE DOI
2212
Measurement, Visualization, Grounding, Genomics,
Image representation, Graph neural networks
BibRef
Yamamoto, T.[Takuma],
Obinata, Y.Y.[Yu-Ya],
Nakayama, O.[Osafumi],
Transformer-based Scene Graph Generation Network With Relational
Attention Module,
ICPR22(2034-2041)
IEEE DOI
2212
Training, Adaptation models, Visualization, Annotations, Genomics,
Training data, Predictive models
BibRef
Kim, M.S.[Min-Sang],
Baek, S.[Seungjun],
ComDensE: Combined Dense Embedding of Relation-aware and Common
Features for Knowledge Graph Completion,
ICPR22(1989-1995)
IEEE DOI
2212
Computational modeling, Neural networks,
Feature extraction, Encoding, Natural language processing
BibRef
Yu, X.[Xiang],
Li, J.[Jie],
Yuan, S.J.[Shi-Jing],
Wang, C.[Chao],
Wu, C.T.[Chen-Tao],
Zero-Shot Scene Graph Generation with Relational Graph Neural
Networks,
ICPR22(1894-1900)
IEEE DOI
2212
Training, Measurement, Visualization, Correlation, Semantics, Genomics,
Feature extraction
BibRef
Shit, S.[Suprosanna],
Koner, R.[Rajat],
Wittmann, B.[Bastian],
Paetzold, J.[Johannes],
Ezhov, I.[Ivan],
Li, H.W.[Hong-Wei],
Pan, J.Z.[Jia-Zhen],
Sharifzadeh, S.[Sahand],
Kaissis, G.[Georgios],
Tresp, V.[Volker],
Menze, B.[Bjoern],
Relationformer: A Unified Framework for Image-to-Graph Generation,
ECCV22(XXXVII:422-439).
Springer DOI
2211
BibRef
Zhang, A.[Ao],
Yao, Y.[Yuan],
Chen, Q.Y.[Qian-Yu],
Ji, W.[Wei],
Liu, Z.Y.[Zhi-Yuan],
Sun, M.[Maosong],
Chua, T.S.[Tat-Seng],
Fine-Grained Scene Graph Generation with Data Transfer,
ECCV22(XXVII:409-424).
Springer DOI
2211
BibRef
Deng, Y.M.[You-Ming],
Li, Y.S.[Yan-Sheng],
Zhang, Y.J.[Yong-Jun],
Xiang, X.[Xiang],
Wang, J.[Jian],
Chen, J.D.[Jing-Dong],
Ma, J.Y.[Jia-Yi],
Hierarchical Memory Learning for Fine-Grained Scene Graph Generation,
ECCV22(XXVII:266-283).
Springer DOI
2211
BibRef
Yang, J.K.[Jing-Kang],
Ang, Y.Z.[Yi Zhe],
Guo, Z.[Zujin],
Zhou, K.Y.[Kai-Yang],
Zhang, W.[Wayne],
Liu, Z.[Ziwei],
Panoptic Scene Graph Generation,
ECCV22(XXVII:178-196).
Springer DOI
2211
BibRef
He, T.[Tao],
Gao, L.[Lianli],
Song, J.[Jingkuan],
Li, Y.F.[Yuan-Fang],
Towards Open-Vocabulary Scene Graph Generation with Prompt-Based
Finetuning,
ECCV22(XXVIII:56-73).
Springer DOI
2211
BibRef
Xu, L.[Li],
Qu, H.X.[Hao-Xuan],
Kuen, J.[Jason],
Gu, J.X.[Jiu-Xiang],
Liu, J.[Jun],
Meta Spatio-Temporal Debiasing for Video Scene Graph Generation,
ECCV22(XXVII:374-390).
Springer DOI
2211
BibRef
Dong, W.[Wei],
Wu, J.S.[Jun-Sheng],
Luo, Y.[Yi],
Ge, Z.Y.[Zong-Yuan],
Wang, P.[Peng],
Node Representation Learning in Graph via Node-to-Neighbourhood
Mutual Information Maximization,
CVPR22(16599-16608)
IEEE DOI
2210
WWW Link. Representation learning, Smoothing methods, Codes,
Computational modeling, Pattern recognition, Mutual information,
Self- semi- meta- unsupervised learning
BibRef
Li, W.[Wei],
Zhang, H.W.[Hai-Wei],
Bai, Q.J.[Qi-Jie],
Zhao, G.Q.[Guo-Qing],
Jiang, N.[Ning],
Yuan, X.J.[Xiao-Jie],
PPDL: Predicate Probability Distribution based Loss for Unbiased
Scene Graph Generation,
CVPR22(19425-19434)
IEEE DOI
2210
Training, Visualization, Analytical models, Computational modeling,
Semantics, Optimization methods, Tail, retrieval, Recognition: detection
BibRef
Teng, Y.[Yao],
Wang, L.M.[Li-Min],
Structured Sparse R-CNN for Direct Scene Graph Generation,
CVPR22(19415-19424)
IEEE DOI
2210
Training, Visualization, Head, Pipelines, Genomics, Detectors,
Object detection, Scene analysis and understanding,
retrieval
BibRef
Dong, X.N.[Xing-Ning],
Gan, T.[Tian],
Song, X.M.[Xue-Meng],
Wu, J.L.[Jian-Long],
Cheng, Y.[Yuan],
Nie, L.Q.[Li-Qiang],
Stacked Hybrid-Attention and Group Collaborative Learning for
Unbiased Scene Graph Generation,
CVPR22(19405-19414)
IEEE DOI
2210
Measurement, Visualization, Image analysis, Codes,
Computational modeling, Pipelines, Vision + X
BibRef
Li, Y.M.[Yi-Ming],
Yang, X.S.[Xiao-Shan],
Xu, C.S.[Chang-Sheng],
Dynamic Scene Graph Generation via Anticipatory Pre-training,
CVPR22(13864-13873)
IEEE DOI
2210
Visualization, Correlation, Triples (Data structure), Semantics,
Predictive models, Transformers, Data mining, Visual reasoning
BibRef
Li, R.J.[Rong-Jie],
Zhang, S.[Songyang],
He, X.M.[Xu-Ming],
SGTR: End-to-end Scene Graph Generation with Transformer,
CVPR22(19464-19474)
IEEE DOI
2210
Visualization, Image analysis, Transformers, Pattern recognition,
Decoding, Bipartite graph, Proposals, Visual reasoning
BibRef
Lyu, X.Y.[Xin-Yu],
Gao, L.L.[Lian-Li],
Guo, Y.Y.[Yu-Yu],
Zhao, Z.[Zhou],
Huang, H.[Hao],
Shen, H.T.[Heng Tao],
Song, J.[Jingkuan],
Fine-Grained Predicates Learning for Scene Graph Generation,
CVPR22(19445-19453)
IEEE DOI
2210
Visualization, Head, Lattices, Tail, Benchmark testing,
Predictive models, Transformers, Visual reasoning
BibRef
Nguyen, E.[Eric],
Bui, T.[Tu],
Swaminathan, V.[Viswanathan],
Collomosse, J.[John],
OSCAR-Net: Object-centric Scene Graph Attention for Image Attribution,
ICCV21(14479-14488)
IEEE DOI
2203
Visualization, Shape, Scalability, Fingerprint recognition,
Transformers, Search problems,
Scene analysis and understanding
BibRef
Yao, Y.[Yuan],
Zhang, A.[Ao],
Han, X.[Xu],
Li, M.D.[Meng-Di],
Weber, C.[Cornelius],
Liu, Z.Y.[Zhi-Yuan],
Wermter, S.[Stefan],
Sun, M.S.[Mao-Song],
Visual Distant Supervision for Scene Graph Generation,
ICCV21(15796-15806)
IEEE DOI
2203
Visualization, Computational modeling, Noise reduction,
Supervised learning, Image representation, Probabilistic logic,
Vision + language
BibRef
Knyazev, B.[Boris],
de Vries, H.[Harm],
Cangea, C.[Catalina],
Taylor, G.W.[Graham W.],
Courville, A.[Aaron],
Belilovsky, E.[Eugene],
Generative Compositional Augmentations for Scene Graph Prediction,
ICCV21(15807-15817)
IEEE DOI
2203
Measurement, Training, Visualization, Training data, Genomics,
Generative adversarial networks,
Visual reasoning and logical representation
BibRef
Cong, Y.[Yuren],
Liao, W.T.[Wen-Tong],
Ackermann, H.[Hanno],
Rosenhahn, B.[Bodo],
Yang, M.Y.[Michael Ying],
Spatial-Temporal Transformer for Dynamic Scene Graph Generation,
ICCV21(16352-16362)
IEEE DOI
2203
Visualization, Semantics, Neural networks, Genomics,
Transformer cores, Transformers, Video analysis and understanding
BibRef
Guo, Y.Y.[Yu-Yu],
Gao, L.L.[Lian-Li],
Wang, X.H.[Xuan-Han],
Hu, Y.X.[Yu-Xuan],
Xu, X.[Xing],
Lu, X.[Xu],
Shen, H.T.[Heng Tao],
Song, J.K.[Jing-Kuan],
From General to Specific: Informative Scene Graph Generation via
Balance Adjustment,
ICCV21(16363-16372)
IEEE DOI
2203
Training, Visualization, Triples (Data structure), Roads, Semantics,
Power line communications, Layout,
Visual reasoning and logical representation
BibRef
Lu, Y.C.[Yi-Chao],
Rai, H.[Himanshu],
Chang, J.[Jason],
Knyazev, B.[Boris],
Yu, G.[Guangwei],
Shekhar, S.[Shashank],
Taylor, G.W.[Graham W.],
Volkovs, M.[Maksims],
Context-aware Scene Graph Generation with Seq2Seq Transformers,
ICCV21(15911-15921)
IEEE DOI
2203
Training, Measurement, Visualization, Computational modeling,
Training data, Predictive models,
Visual reasoning and logical representation
BibRef
Zhong, Y.[Yiwu],
Shi, J.[Jing],
Yang, J.W.[Jian-Wei],
Xu, C.L.[Chen-Liang],
Li, Y.[Yin],
Learning to Generate Scene Graph from Natural Language Supervision,
ICCV21(1803-1814)
IEEE DOI
2203
Training, Visualization, Image recognition, Natural languages,
Detectors, Predictive models, Transformers, Vision + language,
Scene analysis and understanding
BibRef
Lee, W.[Wonhee],
Kim, S.[Sungeun],
Kim, G.[Gunhee],
Contextual Label Transformation for Scene Graph Generation,
ICIP21(2533-2537)
IEEE DOI
2201
Visualization, Head, Annotations, Scalability, Image processing,
Object detection, Scene graph generation, label transformation
BibRef
Zhang, Z.C.[Zhi-Chao],
Dong, J.Y.[Jun-Yu],
Zhao, Q.[Qilu],
Qi, L.[Lin],
Zhang, S.[Shu],
Attention LSTM for Scene Graph Generation,
ICIVC21(264-268)
IEEE DOI
2112
Degradation, Deep learning, Visualization, Fuses, Message passing,
Semantics, Feature extraction, scene graph generation,
message passing
BibRef
Chen, H.[Hao],
Chen, L.[Lin],
Kuang, X.Y.[Xiao-Yun],
Xu, A.D.[Ai-Dong],
Yang, Y.[Yiwei],
A Safe and Intelligent Knowledge Graph Construction Model Suitable
for Smart Gridaper Title,
ICIVC21(253-258)
IEEE DOI
2112
Computational modeling, Smart grids, smart grid, knowledge map,
ternary extraction
BibRef
Yang, G.C.[Geng-Cong],
Zhang, J.Y.[Jing-Yi],
Zhang, Y.[Yong],
Wu, B.Y.[Bao-Yuan],
Yang, Y.[Yujiu],
Probabilistic Modeling of Semantic Ambiguity for Scene Graph
Generation,
CVPR21(12522-12531)
IEEE DOI
2111
Visualization, Uncertainty, Semantics, Diversity reception,
Measurement uncertainty, Predictive models, Linguistics
BibRef
Li, R.J.[Rong-Jie],
Zhang, S.Y.[Song-Yang],
Wan, B.[Bo],
He, X.M.[Xu-Ming],
Bipartite Graph Network with Adaptive Message Passing for Unbiased
Scene Graph Generation,
CVPR21(11104-11114)
IEEE DOI
2111
Training, Visualization, Adaptive systems,
Message passing, Neural networks, Genomics
BibRef
Liu, H.Y.[Heng-Yue],
Yan, N.[Ning],
Mortazavi, M.[Masood],
Bhanu, B.[Bir],
Fully Convolutional Scene Graph Generation,
CVPR21(11541-11551)
IEEE DOI
2111
Measurement, Visualization, Semantics, Pipelines, Genomics,
Object detection, Detectors
BibRef
Suhail, M.[Mohammed],
Mittal, A.[Abhay],
Siddiquie, B.[Behjat],
Broaddus, C.[Chris],
Eledath, J.[Jayan],
Medioni, G.[Gerard],
Sigal, L.[Leonid],
Energy-Based Learning for Scene Graph Generation,
CVPR21(13931-13940)
IEEE DOI
2111
Training, Visualization, Computational modeling,
Genomics, Benchmark testing, Pattern recognition
BibRef
Dhingra, N.[Naina],
Ritter, F.[Florian],
Kunz, A.[Andreas],
BGT-Net: Bidirectional GRU Transformer Network for Scene Graph
Generation,
WiCV21(2150-2159)
IEEE DOI
2109
Visualization, Image edge detection,
Genomics, Pattern recognition, Softening
BibRef
Liao, W.T.[Wen-Tong],
Lan, C.L.[Cui-Ling],
Yang, M.Y.[Michael Ying],
Zeng, W.J.[Wen-Jun],
Rosenhahn, B.[Bodo],
Target-Tailored Source-Transformation for Scene Graph Generation,
MULA21(1663-1671)
IEEE DOI
2109
Visualization, Message passing, Image edge detection, Semantics,
Genomics, Transforms, Object detection
BibRef
Wang, W.B.[Wen-Bin],
Wang, R.P.[Rui-Ping],
Shan, S.G.[Shi-Guang],
Chen, X.L.[Xi-Lin],
Sketching Image Gist: Human-Mimetic Hierarchical Scene Graph Generation,
ECCV20(XIII:222-239).
Springer DOI
2011
BibRef
Zareian, A.[Alireza],
Karaman, S.[Svebor],
Chang, S.F.[Shih-Fu],
Bridging Knowledge Graphs to Generate Scene Graphs,
ECCV20(XXIII:606-623).
Springer DOI
2011
BibRef
Tang, K.H.[Kai-Hua],
Niu, Y.L.[Yu-Lei],
Huang, J.Q.[Jian-Qiang],
Shi, J.X.[Jia-Xin],
Zhang, H.W.[Han-Wang],
Unbiased Scene Graph Generation from Biased Training,
CVPR20(3713-3722)
IEEE DOI
2008
Visualization, Training, Task analysis, Predictive models, Dogs,
Cognition, Genomics
BibRef
Kurosawa, I.[Ikuto],
Kobayashi, T.[Tetsunori],
Hayashi, Y.[Yoshihiko],
Exploring and Exploiting the Hierarchical Structure of a Scene for
Scene Graph Generation,
ICPR21(1422-1429)
IEEE DOI
2105
Visualization, Aggregates, Neural networks, Genomics,
Knowledge discovery, Labeling
BibRef
Lin, X.[Xin],
Ding, C.X.[Chang-Xing],
Zhan, Y.B.[Yi-Bing],
Li, Z.J.[Zi-Jian],
Tao, D.C.[Da-Cheng],
HL-Net: Heterophily Learning Network for Scene Graph Generation,
CVPR22(19454-19463)
IEEE DOI
2210
Visualization, Image analysis, Codes, Message passing, Genomics,
Transformers, Scene analysis and understanding,
Visual reasoning
BibRef
Lin, X.[Xin],
Ding, C.X.[Chang-Xing],
Zhang, J.[Jing],
Zhan, Y.B.[Yi-Bing],
Tao, D.C.[Da-Cheng],
RU-Net: Regularized Unrolling Network for Scene Graph Generation,
CVPR22(19435-19444)
IEEE DOI
2210
Measurement, Visualization, Systematics, Laplace equations,
Image analysis, Correlation, Databases,
Visual reasoning
BibRef
Lin, X.[Xin],
Ding, C.X.[Chang-Xing],
Zeng, J.Q.[Jin-Quan],
Tao, D.C.[Da-Cheng],
GPS-Net: Graph Property Sensing Network for Scene Graph Generation,
CVPR20(3743-3752)
IEEE DOI
2008
Context modeling, Mathematical model, Ear, Visualization,
Message passing, Dogs, Legged locomotion
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Wang, Z.[Zhecan],
You, H.[Haoxuan],
Chang, S.F.[Shih-Fu],
Learning Visual Commonsense for Robust Scene Graph Generation,
ECCV20(XXIII:642-657).
Springer DOI
2011
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Chen, L.,
Zhang, H.,
Xiao, J.,
He, X.,
Pu, S.,
Chang, S.,
Counterfactual Critic Multi-Agent Training for Scene Graph Generation,
ICCV19(4612-4622)
IEEE DOI
2004
biology computing, entropy, genomics, gradient methods, graph theory,
image processing, learning (artificial intelligence),
BibRef
Gkanatsios, N.,
Pitsikalis, V.,
Koutras, P.,
Maragos, P.,
Attention-Translation-Relation Network for Scalable Scene Graph
Generation,
SGRL19(1754-1764)
IEEE DOI
2004
computer graphics, feature extraction,
attention-translation-relation network, background class,
Vision and Language
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Chen, T.S.[Tian-Shui],
Yu, W.H.[Wei-Hao],
Chen, R.Q.[Ri-Quan],
Lin, L.[Liang],
Knowledge-Embedded Routing Network for Scene Graph Generation,
CVPR19(6156-6164).
IEEE DOI
2002
BibRef
Chen, Z.[Zhanwen],
Rezayi, S.[Saed],
Li, S.[Sheng],
More Knowledge, Less Bias: Unbiasing Scene Graph Generation with
Explicit Ontological Adjustment,
WACV23(4012-4021)
IEEE DOI
2302
Training, Visualization, Solid modeling, Source coding,
Image edge detection, Semantics, Knowledge based systems,
Vision + language and/or other modalities
BibRef
Gu, J.X.[Jiu-Xiang],
Zhao, H.D.[Han-Dong],
Lin, Z.[Zhe],
Li, S.[Sheng],
Cai, J.F.[Jian-Fei],
Ling, M.Y.[Ming-Yang],
Scene Graph Generation With External Knowledge and Image Reconstruction,
CVPR19(1969-1978).
IEEE DOI
2002
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Wang, W.B.[Wen-Bin],
Wang, R.P.[Rui-Ping],
Shan, S.G.[Shi-Guang],
Chen, X.L.[Xi-Lin],
Exploring Context and Visual Pattern of Relationship for Scene Graph
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CVPR19(8180-8189).
IEEE DOI
2002
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Khademi, M.[Mahmoud],
Schulte, O.[Oliver],
Dynamic Gated Graph Neural Networks for Scene Graph Generation,
ACCV18(VI:669-685).
Springer DOI
1906
BibRef
Li, Y.K.[Yi-Kang],
Ouyang, W.L.[Wan-Li],
Zhou, B.[Bolei],
Shi, J.P.[Jian-Ping],
Zhang, C.[Chao],
Wang, X.G.[Xiao-Gang],
Factorizable Net: An Efficient Subgraph-Based Framework for Scene Graph
Generation,
ECCV18(I: 346-363).
Springer DOI
1810
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Yang, J.W.[Jian-Wei],
Lu, J.[Jiasen],
Lee, S.[Stefan],
Batra, D.[Dhruv],
Parikh, D.[Devi],
Graph R-CNN for Scene Graph Generation,
ECCV18(I: 690-706).
Springer DOI
1810
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Xu, D.,
Zhu, Y.,
Choy, C.B.,
Fei-Fei, L.[Li],
Scene Graph Generation by Iterative Message Passing,
CVPR17(3097-3106)
IEEE DOI
1711
Image edge detection, Message passing, Predictive models,
Proposals, Semantics, Visualization
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Li, Y.,
Ouyang, W.,
Zhou, B.,
Wang, K.,
Wang, X.,
Scene Graph Generation from Objects, Phrases and Region Captions,
ICCV17(1270-1279)
IEEE DOI
1802
graph theory, image classification, image representation,
neural nets, object detection,
Visualization
BibRef
Chapter on Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants continues in
Network Embedding, Graph Embedding .