Deep Learning for Video Captioning: A Review
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[1] Bernard Ghanem,et al. SST: Single-Stream Temporal Action Proposals , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[2] Zhou Su,et al. Weakly Supervised Dense Video Captioning , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[3] Jiebo Luo,et al. Image Captioning with Semantic Attention , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[4] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[5] Wei Liu,et al. Bidirectional Attentive Fusion with Context Gating for Dense Video Captioning , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[6] C. Lawrence Zitnick,et al. CIDEr: Consensus-based image description evaluation , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[7] Basura Fernando,et al. SPICE: Semantic Propositional Image Caption Evaluation , 2016, ECCV.
[8] Ramakant Nevatia,et al. TALL: Temporal Activity Localization via Language Query , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[9] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[10] Xinlei Chen,et al. Grounded Video Description , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[11] Yongdong Zhang,et al. Learning Multimodal Attention LSTM Networks for Video Captioning , 2017, ACM Multimedia.
[12] 김건중. Multimedia , 1995, The ACS Guide to Scholarly Communication.
[13] Bernard Ghanem,et al. DAPs: Deep Action Proposals for Action Understanding , 2016, ECCV.
[14] Tao Mei,et al. Exploring Visual Relationship for Image Captioning , 2018, ECCV.
[15] Tao Mei,et al. MSR-VTT: A Large Video Description Dataset for Bridging Video and Language , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[16] Christopher Joseph Pal,et al. Describing Videos by Exploiting Temporal Structure , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[17] Yu-Gang Jiang,et al. Semantic Proposal for Activity Localization in Videos via Sentence Query , 2019, AAAI.
[18] Xuelong Li,et al. MAM-RNN: Multi-level Attention Model Based RNN for Video Captioning , 2017, IJCAI.
[19] Marc'Aurelio Ranzato,et al. Sequence Level Training with Recurrent Neural Networks , 2015, ICLR.
[20] Lorenzo Torresani,et al. Learning Spatiotemporal Features with 3D Convolutional Networks , 2014, 2015 IEEE International Conference on Computer Vision (ICCV).
[21] Trevor Darrell,et al. YouTube2Text: Recognizing and Describing Arbitrary Activities Using Semantic Hierarchies and Zero-Shot Recognition , 2013, 2013 IEEE International Conference on Computer Vision.
[22] M. V. Rossum,et al. In Neural Computation , 2022 .
[24] Bernard Ghanem,et al. The ActivityNet Large-Scale Activity Recognition Challenge 2018 Summary , 2018, ArXiv.
[25] Xin Wang,et al. Watch, Listen, and Describe: Globally and Locally Aligned Cross-Modal Attentions for Video Captioning , 2018, NAACL.
[26] Yale Song,et al. TGIF: A New Dataset and Benchmark on Animated GIF Description , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[27] Ronald J. Williams,et al. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning , 2004, Machine Learning.
[28] Yu-Gang Jiang,et al. Motion Guided Spatial Attention for Video Captioning , 2019, AAAI.
[29] Bernard Ghanem,et al. ActivityNet Challenge 2017 Summary , 2017, ArXiv.
[30] Salim Roukos,et al. Bleu: a Method for Automatic Evaluation of Machine Translation , 2002, ACL.
[31] Jinfeng Yi,et al. Attacking Visual Language Grounding with Adversarial Examples: A Case Study on Neural Image Captioning , 2017, ACL.
[32] Thomas G. Dietterich. What is machine learning? , 2020, Archives of Disease in Childhood.
[33] Tao Mei,et al. Jointly Modeling Embedding and Translation to Bridge Video and Language , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[34] Wei Xu,et al. Video Paragraph Captioning Using Hierarchical Recurrent Neural Networks , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[35] Tao Mei,et al. Temporal Deformable Convolutional Encoder-Decoder Networks for Video Captioning , 2019, AAAI.
[36] Yahong Han,et al. Spotting and Aggregating Salient Regions for Video Captioning , 2018, ACM Multimedia.
[37] Christopher Joseph Pal,et al. Using Descriptive Video Services to Create a Large Data Source for Video Annotation Research , 2015, ArXiv.
[38] Tao Mei,et al. Incorporating Copying Mechanism in Image Captioning for Learning Novel Objects , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[39] Siqi Liu,et al. Improved Image Captioning via Policy Gradient optimization of SPIDEr , 2016, 2017 IEEE International Conference on Computer Vision (ICCV).
[40] Alon Lavie,et al. METEOR: An Automatic Metric for MT Evaluation with High Levels of Correlation with Human Judgments , 2007, WMT@ACL.
[41] Sergey Ioffe,et al. Rethinking the Inception Architecture for Computer Vision , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[42] Chenliang Xu,et al. A Thousand Frames in Just a Few Words: Lingual Description of Videos through Latent Topics and Sparse Object Stitching , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.