Academic literature on the topic 'Motion captioning'
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Journal articles on the topic "Motion captioning"
Iwamura, Kiyohiko, Jun Younes Louhi Kasahara, Alessandro Moro, Atsushi Yamashita, and Hajime Asama. "Image Captioning Using Motion-CNN with Object Detection." Sensors 21, no. 4 (February 10, 2021): 1270. http://dx.doi.org/10.3390/s21041270.
Full textChen, Shaoxiang, and Yu-Gang Jiang. "Motion Guided Spatial Attention for Video Captioning." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 8191–98. http://dx.doi.org/10.1609/aaai.v33i01.33018191.
Full textZhao, Hong, Lan Guo, ZhiWen Chen, and HouZe Zheng. "Research on Video Captioning Based on Multifeature Fusion." Computational Intelligence and Neuroscience 2022 (April 28, 2022): 1–14. http://dx.doi.org/10.1155/2022/1204909.
Full textQi, Mengshi, Yunhong Wang, Annan Li, and Jiebo Luo. "Sports Video Captioning via Attentive Motion Representation and Group Relationship Modeling." IEEE Transactions on Circuits and Systems for Video Technology 30, no. 8 (August 2020): 2617–33. http://dx.doi.org/10.1109/tcsvt.2019.2921655.
Full textAhmed, Shakil, A. F. M. Saifuddin Saif, Md Imtiaz Hanif, Md Mostofa Nurannabi Shakil, Md Mostofa Jaman, Md Mazid Ul Haque, Siam Bin Shawkat, et al. "Att-BiL-SL: Attention-Based Bi-LSTM and Sequential LSTM for Describing Video in the Textual Formation." Applied Sciences 12, no. 1 (December 29, 2021): 317. http://dx.doi.org/10.3390/app12010317.
Full textJiang, Wenhui, Yibo Cheng, Linxin Liu, Yuming Fang, Yuxin Peng, and Yang Liu. "Comprehensive Visual Grounding for Video Description." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 3 (March 24, 2024): 2552–60. http://dx.doi.org/10.1609/aaai.v38i3.28032.
Full textKim, Heechan, and Soowon Lee. "A Video Captioning Method Based on Multi-Representation Switching for Sustainable Computing." Sustainability 13, no. 4 (February 19, 2021): 2250. http://dx.doi.org/10.3390/su13042250.
Full textCharmatz, Marc. "Magistrate denies motion to dismiss in cases against Harvard and MIT on web content captioning." Disability Compliance for Higher Education 21, no. 10 (April 20, 2016): 1–3. http://dx.doi.org/10.1002/dhe.30174.
Full textChen, Jin, Xiaofeng Ji, and Xinxiao Wu. "Adaptive Image-to-Video Scene Graph Generation via Knowledge Reasoning and Adversarial Learning." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 1 (June 28, 2022): 276–84. http://dx.doi.org/10.1609/aaai.v36i1.19903.
Full textYang, Jiaji, Esyin Chew, and Pengcheng Liu. "Service humanoid robotics: a novel interactive system based on bionic-companionship framework." PeerJ Computer Science 7 (August 13, 2021): e674. http://dx.doi.org/10.7717/peerj-cs.674.
Full textDissertations / Theses on the topic "Motion captioning"
Radouane, Karim. "Mécanisme d’attention pour le sous-titrage du mouvement humain : Vers une segmentation sémantique et analyse du mouvement interprétables." Electronic Thesis or Diss., IMT Mines Alès, 2024. http://www.theses.fr/2024EMAL0002.
Full textCaptioning tasks mainly focus on images or videos, and seldom on human poses. Yet, poses concisely describe human activities. Beyond text generation quality, we consider the motion caption task as an intermediate step to solve other derived tasks. In this holistic approach, our experiments are centered on the unsupervised learning of semantic motion segmentation and interpretability. We first conduct an extensive literature review of recent methods for human pose estimation, as a central prerequisite for pose-based captioning. Then, we take an interest in pose-representation learning, with an emphasis on the use of spatiotemporal graph-based learning, which we apply and evaluate on a real-world application (protective behavior detection). As a result, we win the AffectMove challenge. Next, we delve into the core of our contributions in motion captioning, where: (i) We design local recurrent attention for synchronous text generation with motion. Each motion and its caption are decomposed into primitives and corresponding sub-captions. We also propose specific metrics to evaluate the synchronous mapping between motion and language segments. (ii) We initiate the construction of a motion-language dataset to enable supervised segmentation. (iii) We design an interpretable architecture with a transparent reasoning process through spatiotemporal attention, showing state-of-the-art results on the two reference datasets, KIT-ML and HumanML3D. Effective tools are proposed for interpretability evaluation and illustration. Finally, we conduct a thorough analysis of potential applications: unsupervised action segmentation, sign language translation, and impact in other scenarios
Books on the topic "Motion captioning"
Sahlin, Ingrid. Tal och undertexter i textade svenska TV-program: Probleminventering och förslag till en analysmodell. Göteborg: Acta Universitatis Gothoburgensis, 2001.
Find full textRobson, Gary D. Closed Captioning Handbook. Taylor & Francis Group, 2004.
Find full textRobson, Gary D. Closed Captioning Handbook. Taylor & Francis Group, 2004.
Find full textRobson, Gary D. Closed Captioning Handbook. Taylor & Francis Group, 2016.
Find full textRobson, Gary D. Closed Captioning Handbook. Taylor & Francis Group, 2004.
Find full textRobson, Gary D. Closed Captioning Handbook. Taylor & Francis Group, 2004.
Find full textRobson, Gary D. The Closed Captioning Handbook. Focal Press, 2004.
Find full textFox, Wendy. Can Integrated Titles Improve the Viewing Experience? Saint Philip Street Press, 2020.
Find full text(Editor), Jorge Diaz-Cintas, Pilar Orero (Editor), and Aline Remael (Editor), eds. Media for All: Subtitling for the Deaf, Audio Description, and Sign Language (Approaches to Translation Studies 30) (Approaches to Translation Studies). Rodopi, 2007.
Find full textBook chapters on the topic "Motion captioning"
Hai-Jew, Shalin. "Image on the Street Is . . ." In Advances in Media, Entertainment, and the Arts, 1–45. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-5225-9821-3.ch001.
Full textConference papers on the topic "Motion captioning"
Iwamura, Kiyohiko, Jun Younes Louhi Kasahara, Alessandro Moro, Atsushi Yamashita, and Hajime Asama. "Potential of Incorporating Motion Estimation for Image Captioning." In 2021 IEEE/SICE International Symposium on System Integration (SII). IEEE, 2021. http://dx.doi.org/10.1109/ieeeconf49454.2021.9382725.
Full textChen, Shaoxiang, and Yu-Gang Jiang. "Motion Guided Region Message Passing for Video Captioning." In 2021 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE, 2021. http://dx.doi.org/10.1109/iccv48922.2021.00157.
Full textBosch Ruiz, Marc, Christopher M. Gifford, Agata Ciesielski, Scott Almes, Rachel Ellison, and Gordon Christie. "Captioning of full motion video from unmanned aerial platforms." In Geospatial Informatics IX, edited by Kannappan Palaniappan, Gunasekaran Seetharaman, and Peter J. Doucette. SPIE, 2019. http://dx.doi.org/10.1117/12.2518163.
Full textHu, Yimin, Guorui Yu, Yuejie Zhang, Rui Feng, Tao Zhang, Xuequan Lu, and Shang Gao. "Motion-Aware Video Paragraph Captioning via Exploring Object-Centered Internal Knowledge." In ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2023. http://dx.doi.org/10.1109/icassp49357.2023.10096625.
Full textQi, Mengshi, Yunhong Wang, Annan Li, and Jiebo Luo. "Sports Video Captioning by Attentive Motion Representation based Hierarchical Recurrent Neural Networks." In MM '18: ACM Multimedia Conference. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3265845.3265851.
Full textMori, Yuki, Tsubasa Hirakawa, Takayoshi Yamashita, and Hironobu Fujiyoshi. "Image Captioning for Near-Future Events from Vehicle Camera Images and Motion Information." In 2021 IEEE Intelligent Vehicles Symposium (IV). IEEE, 2021. http://dx.doi.org/10.1109/iv48863.2021.9575562.
Full textKaushik, Prashant, Vikas Saxena, and Amarjeet Prajapati. "A Novel Method for Sequence Generation for Video Captioning by Estimating the Objects Motion in Temporal Domain." In 2024 2nd International Conference on Disruptive Technologies (ICDT). IEEE, 2024. http://dx.doi.org/10.1109/icdt61202.2024.10489570.
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