Energy-Based Learning for Scene Graph Generation

[1]  Yejin Choi,et al.  Neural Motifs: Scene Graph Parsing with Global Context , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[2]  Fu Jie Huang,et al.  A Tutorial on Energy-Based Learning , 2006 .

[3]  Wei Liu,et al.  Learning to Compose Dynamic Tree Structures for Visual Contexts , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[4]  Li Fei-Fei,et al.  Image Generation from Scene Graphs , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[5]  Gang Wang,et al.  Unpaired Image Captioning via Scene Graph Alignments , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[6]  Yann LeCun,et al.  Loss Functions for Discriminative Training of Energy-Based Models , 2005, AISTATS.

[7]  Mohammad Norouzi,et al.  Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One , 2019, ICLR.

[8]  Richard S. Zemel,et al.  Gated Graph Sequence Neural Networks , 2015, ICLR.

[9]  Kaiming He,et al.  Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[10]  Yee Whye Teh,et al.  Bayesian Learning via Stochastic Gradient Langevin Dynamics , 2011, ICML.

[11]  Christopher D. Manning,et al.  GQA: A New Dataset for Real-World Visual Reasoning and Compositional Question Answering , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[12]  Byoung-Tak Zhang,et al.  Bilinear Attention Networks , 2018, NeurIPS.

[13]  Xiaogang Wang,et al.  Factorizable Net: An Efficient Subgraph-based Framework for Scene Graph Generation , 2018, ECCV.

[14]  Ji Zhang,et al.  Graphical Contrastive Losses for Scene Graph Parsing , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[15]  Jianqiang Huang,et al.  Unbiased Scene Graph Generation From Biased Training , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[16]  Aaron C. Courville,et al.  Graph Density-Aware Losses for Novel Compositions in Scene Graph Generation , 2020, BMVC.

[17]  Shih-Fu Chang,et al.  Bridging Knowledge Graphs to Generate Scene Graphs , 2020, ECCV.

[18]  Jia Deng,et al.  Pixels to Graphs by Associative Embedding , 2017, NIPS.

[19]  Zhuowen Tu,et al.  Aggregated Residual Transformations for Deep Neural Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[20]  Jinquan Zeng,et al.  GPS-Net: Graph Property Sensing Network for Scene Graph Generation , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[21]  Shih-Fu Chang,et al.  Learning Visual Commonsense for Robust Scene Graph Generation: Supplementary Material , 2020 .

[22]  Lukasz Kaiser,et al.  Attention is All you Need , 2017, NIPS.

[23]  Yang Song,et al.  Generative Modeling by Estimating Gradients of the Data Distribution , 2019, NeurIPS.

[24]  Trevor Darrell,et al.  Learning Canonical Representations for Scene Graph to Image Generation , 2019, ECCV.

[25]  Michael S. Bernstein,et al.  Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations , 2016, International Journal of Computer Vision.

[26]  Stefan Lee,et al.  Graph R-CNN for Scene Graph Generation , 2018, ECCV.

[27]  Michael S. Bernstein,et al.  Visual Relationship Detection with Language Priors , 2016, ECCV.

[28]  Igor Mordatch,et al.  Implicit Generation and Modeling with Energy Based Models , 2019, NeurIPS.

[29]  Danfei Xu,et al.  Scene Graph Generation by Iterative Message Passing , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[30]  Jianfei Cai,et al.  Auto-Encoding Scene Graphs for Image Captioning , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).