Hierarchy parsing for image captioning
WebHierarchy Parsing for Image Captioning Ting Yao, Yingwei Pan, Yehao Li, and Tao Mei JD AI Research, Beijing, China ftingyao.ustc, panyw.ustc, [email protected], … Web数据集(Dataset) 暂无分类 检测 图像目标检测(2D Object Detection) 视频目标检测(Video Object Detection) 三维目标检测(3D object detection) 人物交互检测(HOI Detection) 伪装目标检测(Camouflaged Object Detection) 旋转目标检测(Rotation Object Detection) 显著性检测(Saliency Object Detection) 图像异常检测(Anomally Detection in Image ...
Hierarchy parsing for image captioning
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Web29 de mar. de 2024 · The transformer architecture has been the dominant framework for today's image captioning tasks because of its superior performance. However, existing methods based on transformer often lack the integrated use of multi-level semantic information and are weak in maintaining the relevance of captions to the image.
Web9 de dez. de 2024 · Figure 1. Comparisons of different image captioning models. Top: A general image captioning pipeline. Bottom: (a). Prevailing conventional models [25, 39, 79] which are based on an object detector to extract regional features. Object tags [38, 79] can be optionally used to assist the text generation through a multi-modal decoder network. … Web18 de nov. de 2024 · Yao T, Pan Y, Li Y, et al. Hierarchy parsing for image captioning. In: Proceedings of the IEEE International Conference on Computer Vision, 2024. 2621–2629. Jiang W, Ma L, Jiang Y G, et al. Recurrent fusion network for image captioning. In: Proceedings of the European Conference on Computer Vision, 2024. 499–515
WebHierarchy Parsing for Image Captioning. Ting Yao, Yingwei Pan, Yehao Li, Tao Mei; Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), … WebYao, T., Pan, Y., Li, Y., Mei, T.: Hierarchy parsing for image captioning. In: IEEE International Conference on Computer Vision, pp. 2621–2629 (2024) Google Scholar; 27. Yu Q Xiao X Zhang C Song L Pan C Extracting effective image attributes with refined universal detection Sensors 2024 21 1 95 10.3390/s21010095 Google Scholar
Web1 de out. de 2024 · Abstract Image captioning is a typical cross-modal task, which aims to automatically describe the main content of an image with a complete and natural sentence. ... Li Y., Mei T., Hierarchy parsing for image captioning, in: Proceedings of the IEEE International Conference on Computer Vision, ...
Web18 de fev. de 2024 · HIP proposes adding a hierarchy parsing structure to the encoder, which resolves the image into a tree structure and utilises more information. RDN ... For … fishergate preston car parkWeb13 de jan. de 2024 · Stylized image captioning as presented in prior work aims to generate captions that reflect characteristics beyond a factual ... Li, Y., Mei, T.: Hierarchy parsing for image captioning. In: ICCV, pp. 2621–2629 (2024) Google Scholar You, Q., Jin, H., Luo, J.: Image captioning at will: a versatile scheme for effectively ... canadian citizenship office phone numberWeb14 de abr. de 2024 · Download Citation Image Captioning with Local-Global Visual Interaction Network Existing attention based image captioning approaches treat local feature and global feature in the image ... fishergate postern towerWeb12 de out. de 2024 · 第六十二周学习笔记 论文阅读概述. Hierarchy Parsing for Image Captioning: This article introduces a hierarchy encoder for image captioning which … fishergate postern tower yorkWebHierarchy Parsing for Image Captioning Ting Yao Yingwei Pan Yehao Li and Tao Mei JD AI Research Beijing China {tingyaoustc panywustc yehaolisysu}@gmailcom tmei@jdcom Abstract… canadian citizenship online calculatorWeb12 de out. de 2024 · Hierarchy Parsing for Image Captioning. In Proc. IEEE ICCV. 2621--2629. Google Scholar; Ren Yi, Liu Jinglin, Tan Xu, Zhao Sheng, Zhao Zhou, and Liu Tie-Yan. 2024. A Study of Non-autoregressive Model for Sequence Generation. arXiv preprint arXiv:2004.10454 (2024). Google Scholar; Cited By View all. Index Terms. Iterative Back ... fishergate norwichWeb25 de fev. de 2024 · 3.1 Transformer Layer. A transformer consists of a stack of multi-head dot-product attention based transformer refining layer. In each layer, for a given input \(A \in \mathbb {R}^{N\times D}\), consisting of N entries of D dimensions. In natural language processing, the input entry can be the embedded feature of a word in a sentence, and in … canadian citizenship online login