mlsanityData to 7 Oct 2026

Convolutional Image Captioning

arXiv 1711.09151 ↗First posted 24 Nov 2017cs.CVcited by 52

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Abstract (arXiv)

Image captioning is an important but challenging task, applicable to virtual assistants, editing tools, image indexing, and support of the disabled. Its challenges are due to the variability and ambiguity of possible image descriptions. In recent years significant progress has been made in image captioning, using Recurrent Neural Networks powered by long-short-term-memory (LSTM) units. Despite mitigating the vanishing gradient problem, and despite their compelling ability to memorize dependencies, LSTM units are complex and inherently sequential across time. To address this issue, recent work has shown benefits of convolutional networks for machine translation and conditional image generation. Inspired by their success, in this paper, we develop a convolutional image captioning technique. We demonstrate its efficacy on the challenging MSCOCO dataset and demonstrate performance on par with the baseline, while having a faster training time per number of parameters. We also perform a detailed analysis, providing compelling reasons in favor of convolutional language generation approaches.

Key facts. Cited by 52 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Nov 2017.

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Citing papers per year: 2021: 18; 2022: 18; 2023: 5; 2024: 6; 2025: 5.

52 papers.

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  1. 2021Image Retrieval on Real-life Images with Pre-trained Vision-and-Language Modelscited by 244
  2. 2021ZeroCap: Zero-Shot Image-to-Text Generation for Visual-Semantic Arithmeticcited by 150
  3. 2021From Show to Tell: A Survey on Deep Learning-based Image Captioningcited by 137
  4. 2022Vision-Language Pre-training: Basics, Recent Advances, and Future Trendscited by 117
  5. 2024Context-Guided Spatio-Temporal Video Groundingcited by 45
  6. 2022Deep Learning Approaches on Image Captioning: A Reviewcited by 43
  7. 2025MMDocIR: Benchmarking Multimodal Retrieval for Long Documentscited by 43
  8. 2022Retrieval-Augmented Transformer for Image Captioningcited by 38
  9. 2022Measuring Representational Harms in Image Captioningcited by 36
  10. 2022M^4I: Multi-modal Models Membership Inferencecited by 30
  11. 2023Multi-modal Machine Learning in Engineering Design: A Review and Future Directionscited by 27
  12. 2023Survey of Social Bias in Vision-Language Modelscited by 26
38 more
  1. 2021ReFormer: The Relational Transformer for Image Captioningcited by 23
  2. 2021Dynamic Attention guided Multi-Trajectory Analysis for Single Object Trackingcited by 17
  3. 2023MMNet: Multi-Collaboration and Multi-Supervision Network for Sequential Deepfake Detectioncited by 15
  4. 2021Journalistic Guidelines Aware News Image Captioningcited by 14
  5. 2022CaMEL: Mean Teacher Learning for Image Captioningcited by 14
  6. 2021Group-based Distinctive Image Captioning with Memory Attentioncited by 13
  7. 2021Neural Attention for Image Captioning: Review of Outstanding Methodscited by 11
  8. 2023Diagnosing Human-object Interaction Detectorscited by 11
  9. 2021X-modaler: A Versatile and High-performance Codebase for Cross-modal Analyticscited by 10
  10. 2021Discrete-continuous Action Space Policy Gradient-based Attention for Image-Text Matchingcited by 8
  11. 2021Multi-Modal Image Captioning for the Visually Impairedcited by 8
  12. 2021Automatic Generation of Descriptive Titles for Video Clips Using Deep Learningcited by 7
  13. 2022On Distinctive Image Captioning via Comparing and Reweightingcited by 7
  14. 2021Image Captioning using Deep Stacked LSTMs, Contextual Word Embeddings and Data Augmentationcited by 5
  15. 2021Bornon: Bengali Image Captioning with Transformer-based Deep learning approachcited by 5
  16. 2022Beyond Greedy Search: Tracking by Multi-Agent Reinforcement Learning-based Beam Searchcited by 5
  17. 2022Improving Radiology Summarization with Radiograph and Anatomy Promptscited by 4
  18. 2024AI Readiness in Healthcare through Storytelling XAIcited by 4
  19. 2021Comparative evaluation of CNN architectures for Image Caption Generationcited by 3
  20. 2022Diverse Image Captioning with Grounded Stylecited by 3
  21. 2022Are metrics measuring what they should? An evaluation of image captioning task metricscited by 2
  22. 2025Multiple Choice Learning of Low-Rank Adapters for Language Modelingcited by 2
  23. 2021Goal-driven text descriptions for imagescited by 1
  24. 2021Cross Modification Attention Based Deliberation Model for Image Captioningcited by 1
  25. 2022Do Smart Glasses Dream of Sentimental Visions? Deep Emotionship Analysis for Eyewear Devicescited by 1
  26. 2024Pixels to Prose: Understanding the art of Image Captioningcited by 1
  27. 2025Siamese-Driven Optimization for Low-Resolution Image Latent Embedding in Image Captioningcited by 1
  28. 2021Analysis of Convolutional Decoder for Image Caption Generationcited by 0
  29. 2022Interactive Attention AI to translate low light photos to captions for night scene understanding in women safetycited by 0
  30. 2022An Integrated Approach for Video Captioning and Applicationscited by 0
  31. 2022Controllable Image Captioningcited by 0
  32. 2022Aesthetic Attributes Assessment of Images with AMANv2 and DPC-CaptionsV2cited by 0
  33. 2022Facial Expression Recognition and Image Description Generation in Vietnamesecited by 0
  34. 2022Overcoming Catastrophic Forgetting by XAIcited by 0
  35. 2023GEST: the Graph of Events in Space and Time as a Common Representation between Vision and Languagecited by 0
  36. 2024Compressed Image Captioning using CNN-based Encoder-Decoder Frameworkcited by 0
  37. 2024Surveying the Landscape of Image Captioning Evaluation: A Comprehensive Taxonomy, Trends and Metrics Analysiscited by 0
  38. 2024Y-MAP-Net: Real-time depth, normals, segmentation, multi-label captioning and 2D human pose in RGB imagescited by 0

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