視覺問答VQA知識資料全集
阿新 • • 發佈：2018-12-11
- Kushal Kafle, and Christopher Kanan. Visual question answering: Datasets, algorithms, and future challenges. Computer Vision and Image Understanding [2017].
- [https://arxiv.org/abs/1610.01465]
- Justin Johnson, Bharath Hariharan, Laurens van der Maaten, Li Fei-Fei, C. Lawrence Zitnick, Ross Girshick, CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning, CVPR 2017.
- [http://vision.stanford.edu/pdf/johnson2017cvpr.pdf]
- Justin Johnson, Bharath Hariharan, Laurens van der Maaten, Judy Hoffman, Li Fei-Fei, C. Lawrence Zitnick, Ross Girshick, Inferring and Executing Programs for Visual Reasoning, arXiv:1705.03633, 2017. [https://arxiv.org/abs/1705.03633]
- Ronghang Hu, Jacob Andreas, Marcus Rohrbach, Trevor Darrell, Kate Saenko, Learning to Reason: End-to-End Module Networks for Visual Question Answering, arXiv:1704.05526, 2017. [https://arxiv.org/abs/1704.05526]
- Adam Santoro, David Raposo, David G.T. Barrett, Mateusz Malinowski, Razvan Pascanu, Peter Battaglia, Timothy Lillicrap, A simple neural network module for relational reasoning, arXiv:1706.01427, 2017. [https://arxiv.org/abs/1706.01427]
- Hedi Ben-younes, Remi Cadene, Matthieu Cord, Nicolas Thome: MUTAN: Multimodal Tucker Fusion for Visual Question Answering [https://arxiv.org/pdf/1705.06676.pdf] [https://github.com/Cadene/vqa.pytorch]
- Vahid Kazemi, Ali Elqursh, Show, Ask, Attend, and Answer: A Strong Baseline For Visual Question Answering, arXiv:1704.03162, 2016. [https://arxiv.org/abs/1704.03162] [https://github.com/Cyanogenoid/pytorch-vqa]
- Kushal Kafle, and Christopher Kanan. An Analysis of Visual Question Answering Algorithms. arXiv:1703.09684, 2017. [https://arxiv.org/abs/1703.09684]
- Hyeonseob Nam, Jung-Woo Ha, Jeonghee Kim, Dual Attention Networks for Multimodal Reasoning and Matching, arXiv:1611.00471, 2016. [https://arxiv.org/abs/1611.00471]
- Jin-Hwa Kim, Kyoung Woon On, Jeonghee Kim, Jung-Woo Ha, Byoung-Tak Zhang, Hadamard Product for Low-rank Bilinear Pooling, arXiv:1610.04325, 2016. [https://arxiv.org/abs/1610.04325]
- Akira Fukui, Dong Huk Park, Daylen Yang, Anna Rohrbach, Trevor Darrell, Marcus Rohrbach, Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding, arXiv:1606.01847, 2016. [https://arxiv.org/abs/1606.01847] [https://github.com/akirafukui/vqa-mcb]
- Kuniaki Saito, Andrew Shin, Yoshitaka Ushiku, Tatsuya Harada, DualNet: Domain-Invariant Network for Visual Question Answering. arXiv:1606.06108v1, 2016. [https://arxiv.org/pdf/1606.06108.pdf]
- Arijit Ray, Gordon Christie, Mohit Bansal, Dhruv Batra, Devi Parikh, Question Relevance in VQA: Identifying Non-Visual And False-Premise Questions, arXiv:1606.06622, 2016. [https://arxiv.org/pdf/1606.06622v1.pdf]
- Hyeonwoo Noh, Bohyung Han, Training Recurrent Answering Units with Joint Loss Minimization for VQA, arXiv:1606.03647, 2016. [http://arxiv.org/abs/1606.03647v1]
- Jiasen Lu, Jianwei Yang, Dhruv Batra, Devi Parikh, Hierarchical Question-Image Co-Attention for Visual Question Answering, arXiv:1606.00061, 2016. [https://arxiv.org/pdf/1606.00061v2.pdf] [https://github.com/jiasenlu/HieCoAttenVQA]
- Jin-Hwa Kim, Sang-Woo Lee, Dong-Hyun Kwak, Min-Oh Heo, Jeonghee Kim, Jung-Woo Ha, Byoung-Tak Zhang, Multimodal Residual Learning for Visual QA, arXiv:1606.01455, 2016. [https://arxiv.org/pdf/1606.01455v1.pdf]
- Peng Wang, Qi Wu, Chunhua Shen, Anton van den Hengel, Anthony Dick, FVQA: Fact-based Visual Question Answering, arXiv:1606.05433, 2016. [https://arxiv.org/pdf/1606.05433.pdf]
- Ilija Ilievski, Shuicheng Yan, Jiashi Feng, A Focused Dynamic Attention Model for Visual Question Answering, arXiv:1604.01485. [https://arxiv.org/pdf/1604.01485v1.pdf]
- Yuke Zhu, Oliver Groth, Michael Bernstein, Li Fei-Fei, Visual7W: Grounded Question Answering in Images, CVPR 2016. [http://arxiv.org/abs/1511.03416]
- Hyeonwoo Noh, Paul Hongsuck Seo, and Bohyung Han, Image Question Answering using Convolutional Neural Network with Dynamic Parameter Prediction, CVPR, 2016.[http://arxiv.org/pdf/1511.05756.pdf]
- Jacob Andreas, Marcus Rohrbach, Trevor Darrell, Dan Klein, Learning to Compose Neural Networks for Question Answering, NAACL 2016. [http://arxiv.org/pdf/1601.01705.pdf]
- Jacob Andreas, Marcus Rohrbach, Trevor Darrell, Dan Klein, Deep compositional question answering with neural module networks, CVPR 2016. [https://arxiv.org/abs/1511.02799]
- Zichao Yang, Xiaodong He, Jianfeng Gao, Li Deng, Alex Smola, Stacked Attention Networks for Image Question Answering, CVPR 2016. [http://arxiv.org/abs/1511.02274] [https://github.com/JamesChuanggg/san-torch]
- Kevin J. Shih, Saurabh Singh, Derek Hoiem, Where To Look: Focus Regions for Visual Question Answering, CVPR, 2015. [http://arxiv.org/pdf/1511.07394v2.pdf]
- Kan Chen, Jiang Wang, Liang-Chieh Chen, Haoyuan Gao, Wei Xu, Ram Nevatia, ABC-CNN: An Attention Based Convolutional Neural Network for Visual Question Answering, arXiv:1511.05960v1, Nov 2015. [http://arxiv.org/pdf/1511.05960v1.pdf]
- Huijuan Xu, Kate Saenko, Ask, Attend and Answer: Exploring Question-Guided Spatial Attention for Visual Question Answering, arXiv:1511.05234v1, Nov 2015. [http://arxiv.org/abs/1511.05234]
- Kushal Kafle and Christopher Kanan, Answer-Type Prediction for Visual Question Answering, CVPR 2016. [http://www.cv-foundation.org/openaccess/content_cvpr_2016/html/Kafle_Answer-Type_Prediction_for_CVPR_2016_paper.html]
- Stanislaw Antol, Aishwarya Agrawal, Jiasen Lu, Margaret Mitchell, Dhruv Batra, C. Lawrence Zitnick, Devi Parikh, VQA: Visual Question Answering, ICCV, 2015. [http://arxiv.org/pdf/1505.00468]
- Stanislaw Antol, Aishwarya Agrawal, Jiasen Lu, Margaret Mitchell, Dhruv Batra, C. Lawrence Zitnick, Devi Parikh, VQA: Visual Question Answering, ICCV, 2015. [http://arxiv.org/pdf/1505.00468] [https://github.com/JamesChuanggg/VQA-tensorflow]
- Bolei Zhou, Yuandong Tian, Sainbayar Sukhbaatar, Arthur Szlam, Rob Fergus, Simple Baseline for Visual Question Answering, arXiv:1512.02167v2, Dec 2015. [http://arxiv.org/abs/1512.02167]
- Hauyuan Gao, Junhua Mao, Jie Zhou, Zhiheng Huang, Lei Wang, Wei Xu, Are You Talking to a Machine? Dataset and Methods for Multilingual Image Question Answering, NIPS 2015. [http://arxiv.org/pdf/1505.05612.pdf]
- Mateusz Malinowski, Marcus Rohrbach, Mario Fritz, Ask Your Neurons: A Neural-based Approach to Answering Questions about Images, ICCV 2015. [http://arxiv.org/pdf/1505.01121v3.pdf]
- Mengye Ren, Ryan Kiros, Richard Zemel, Exploring Models and Data for Image Question Answering, ICML 2015. [http://arxiv.org/pdf/1505.02074.pdf]
- Mateusz Malinowski, Mario Fritz, Towards a Visual Turing Challe, NIPS Workshop 2015. [http://arxiv.org/abs/1410.8027]
- Mateusz Malinowski, Mario Fritz, A Multi-World Approach to Question Answering about Real-World Scenes based on Uncertain Input, NIPS 2014. [http://arxiv.org/pdf/1410.0210v4.pdf]