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Chinese Image Captioning via Fuzzy Attention-based DenseNet-BiLSTM
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Every Picture Tells a Story: Generating Sentences from Images
inferredcites →https://doi.org/10.1016/j.ins.2012.07.022openalex-snapshot
Effectiveness of template detection on noise reduction and websites summarization
inferredcites →https://doi.org/10.1109/cvpr.1993.341010openalex-snapshot
Proceedings of IEEE Conference on Computer Vision and Pattern Recognition
inferredcites →https://doi.org/10.1109/cvpr.2015.7298594openalex-snapshot
Going deeper with convolutions
inferredcites →https://doi.org/10.1109/cvpr.2015.7298754openalex-snapshot
From captions to visual concepts and back
inferredcites →https://doi.org/10.1109/cvpr.2015.7298935openalex-snapshot
Show and tell: A neural image caption generator
inferredcites →https://doi.org/10.1109/cvpr.2015.7299087openalex-snapshot
CIDEr: Consensus-based image description evaluation
inferredcites →https://doi.org/10.1109/cvpr.2016.29openalex-snapshot
What Value Do Explicit High Level Concepts Have in Vision to Language Problems?
inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot
Deep Residual Learning for Image Recognition
inferredcites →https://doi.org/10.1109/cvpr.2017.127openalex-snapshot
Semantic Compositional Networks for Visual Captioning
inferredcites →https://doi.org/10.1109/cvpr.2017.128openalex-snapshot
Deep Reinforcement Learning-Based Image Captioning with Embedding Reward
inferredcites →https://doi.org/10.1109/cvpr.2017.131openalex-snapshot
Self-Critical Sequence Training for Image Captioning
inferredcites →https://doi.org/10.1109/cvpr.2017.345openalex-snapshot
Knowing When to Look: Adaptive Attention via a Visual Sentinel for Image Captioning
inferredcites →https://doi.org/10.1109/cvpr.2017.667openalex-snapshot
SCA-CNN: Spatial and Channel-Wise Attention in Convolutional Networks for Image Captioning
inferredcites →https://doi.org/10.1109/cvpr.2018.00146openalex-snapshot
GroupCap: Group-Based Image Captioning with Structured Relevance and Diversity Constraints
inferredcites →https://doi.org/10.1109/cvpr.2018.00636openalex-snapshot
Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering
inferredcites →https://doi.org/10.1109/iccv.2015.277openalex-snapshot
Guiding the Long-Short Term Memory Model for Image Caption Generation
inferredcites →https://doi.org/10.1109/tpami.2012.162openalex-snapshot
BabyTalk: Understanding and Generating Simple Image Descriptions
inferredcites →https://doi.org/10.1162/tacl_a_00177openalex-snapshot
Grounded Compositional Semantics for Finding and Describing Images with Sentences
inferredcites →https://doi.org/10.3115/981311openalex-snapshot
Proceedings of the 21st annual meeting on Association for Computational Linguistics -
inferredcites →https://doi.org/10.48550/arxiv.1409.2329openalex-snapshot
Recurrent Neural Network Regularization
inferredcites →https://doi.org/10.48550/arxiv.1410.1090openalex-snapshot
Explain Images with Multimodal Recurrent Neural Networks
inferredcites →https://doi.org/10.5555/2566972.2566993openalex-snapshot
Framing image description as a ranking task
inferredcites →https://doi.org/10.5555/3013558.3013571openalex-snapshot
Automatic description generation from images
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