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Attention Based Encoder Decoder Model for Video Captioning in Nepali (2023)

arXiv 2312.07418 ↗First posted 12 Dec 2023cs.CVcited by 0

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Abstract (arXiv)

Video captioning in Nepali, a language written in the Devanagari script, presents a unique challenge due to the lack of existing academic work in this domain. This work develops a novel encoder-decoder paradigm for Nepali video captioning to tackle this difficulty. LSTM and GRU sequence-to-sequence models are used in the model to produce related textual descriptions based on features retrieved from video frames using CNNs. Using Google Translate and manual post-editing, a Nepali video captioning dataset is generated from the Microsoft Research Video Description Corpus (MSVD) dataset created using Google Translate, and manual post-editing work. The efficiency of the model for Devanagari-scripted video captioning is demonstrated by BLEU, METOR, and ROUGE measures, which are used to assess its performance.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 14 of its 31 references that are in the map. First posted on arXiv 12 Dec 2023.

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14 of 31 references.

References · 14

  1. 2014Neural Machine Translation by Jointly Learning to Align and Translatecited by 4,530
  2. 2014CIDEr: Consensus-based Image Description Evaluationcited by 2,027
  3. 2016Temporal Segment Networks: Towards Good Practices for Deep Action Recognitioncited by 899
  4. 2021SwinBERT: End-to-End Transformers with Sparse Attention for Video Captioningcited by 161
  5. 2015Sequence to Sequence -- Video to Textcited by 157
  6. 2014Translating Videos to Natural Language Using Deep Recurrent Neural Networkscited by 95
  7. 2021Interventional Video Grounding with Dual Contrastive Learningcited by 94
  8. 2019Memory-Attended Recurrent Network for Video Captioningcited by 65
  9. 2017Appearance-and-Relation Networks for Video Classificationcited by 61
  10. 2019Spatio-Temporal Dynamics and Semantic Attribute Enriched Visual Encoding for Video Captioningcited by 60
  11. 2017Video Captioning via Hierarchical Reinforcement Learningcited by 47
  12. 2018Watch, Listen, and Describe: Globally and Locally Aligned Cross-Modal Attentions for Video Captioningcited by 21
2 more
  1. 2020SBAT: Video Captioning with Sparse Boundary-Aware Transformercited by 12
  2. 2021Bangla Image Caption Generation through CNN-Transformer based Encoder-Decoder Networkcited by 2

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