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Semantic Embedding Guided Attention with Explicit Visual Feature Fusion for Video Captioning

https://doi.org/10.1145/3550276
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/s11263-015-0816-yopenalex-snapshot
ImageNet Large Scale Visual Recognition Challenge
inferredcites →https://doi.org/10.1109/tip.2017.2695887openalex-snapshot
A General Framework for Edited Video and Raw Video Summarization
inferredcites →https://doi.org/10.1109/tip.2018.2846664openalex-snapshot
Sequential Video VLAD: Training the Aggregation Locally and Temporally
inferredcites →https://doi.org/10.1109/tip.2019.2916757openalex-snapshot
CAM-RNN: Co-Attention Model Based RNN for Video Captioning
inferredcites →https://doi.org/10.1109/tmm.2017.2729019openalex-snapshot
Video Captioning With Attention-Based LSTM and Semantic Consistency
inferredcites →https://doi.org/10.1145/3271485openalex-snapshot
Image Captioning via Semantic Guidance Attention and Consensus Selection Strategy
inferredcites →https://doi.org/10.1145/3303083openalex-snapshot
Rich Visual and Language Representation with Complementary Semantics for Video Captioning
inferredcites →https://doi.org/10.1145/3320061openalex-snapshot
Spatiotemporal-Textual Co-Attention Network for Video Question Answering
inferredcites →https://doi.org/10.1145/3436494openalex-snapshot
Visual Semantic-Based Representation Learning Using Deep CNNs for Scene Recognition
inferredcites →https://doi.org/10.3115/v1/w14-3348openalex-snapshot
Meteor Universal: Language Specific Translation Evaluation for Any Target Language

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/s00530-025-01787-5openalex-snapshot
Refined linguistic deliberation for video captioning via cascade transformer and LSTM
inferred← citeshttps://doi.org/10.1016/j.cviu.2026.104853openalex-snapshot
Semantic-Weighted Spatio-Temporal Graphs for Structured Video Understanding and Captioning
inferred← citeshttps://doi.org/10.1016/j.eswa.2026.133544openalex-snapshot
ViS2T: A vision and scene graph to text model for captive giant panda video captioning
inferred← citeshttps://doi.org/10.1093/comjnl/bxaf087openalex-snapshot
EDTC: enhanced depth of text comprehension in automated audio captioning
inferred← citeshttps://doi.org/10.1109/icip49359.2023.10223123openalex-snapshot
A Global-Local Contrastive Learning Framework for Video Captioning
inferred← citeshttps://doi.org/10.1109/tkde.2024.3447878openalex-snapshot
AME-LSIFT: Attention-Aware Multi-Label Ensemble With Label Subset-SpecIfic FeaTures
inferred← citeshttps://doi.org/10.1145/3587252openalex-snapshot
Video Captioning by Learning from Global Sentence and Looking Ahead
inferred← citeshttps://doi.org/10.1145/3588572openalex-snapshot
Semantic Enhanced Video Captioning with Multi-feature Fusion
inferred← citeshttps://doi.org/10.1145/3633334openalex-snapshot
Sentiment-Oriented Transformer-Based Variational Autoencoder Network for Live Video Commenting
inferred← citeshttps://doi.org/10.1145/3679203openalex-snapshot
Action-aware Linguistic Skeleton Optimization Network for Non-autoregressive Video Captioning
inferred← citeshttps://doi.org/10.1145/3688804openalex-snapshot
MMICT: Boosting Multi-Modal Fine-Tuning with In-Context Examples
inferred← citeshttps://doi.org/10.1145/3705322openalex-snapshot
Protein Captioning: Bridging the Gap between Protein Sequences and Natural Languages
inferred← citeshttps://doi.org/10.1145/3712059openalex-snapshot
Dense Video Captioning: A Survey of Techniques, Datasets and Evaluation Protocols
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