2024 Masked non-autoregressive image captioning

Masked non-autoregressive image captioning

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Web18 de may. de 2024 · A partially nonautoregressive model was introduced in [75], which was able to retain the accuracy of autoregressive models and enjoy the speedup of … Web12 de mar. de 2024 · Non-Autoregressive Coarse-to-Fine Video Captioning. PyTorch Implementation of the paper: Non-Autoregressive Coarse-to-Fine Video Captioning (AAAI2024) Bang Yang, Yuexian Zou*, Fenglin Liu and Can Zhang. or . Updates [30 Aug 2024] Update the out-of-date links. [16 Jun 2024] Add detailed instuctions for extracting …

Masked Non-Autoregressive Image Captioning – arXiv Vanity

Web- "Masked Non-Autoregressive Image Captioning" Table 1: Performance comparisons with different evaluation metrics in offline testing. The masking ratio set of MNIC are all … WebMasked Non-Autoregressive Image Captioning. arXiv preprint arXiv:1906.00717 (2024). Google Scholar; Lianli Gao, Kaixuan Fan, Jingkuan Song, Xianglong Liu, Xing Xu, and … monahans workers\u0027 compensation lawyer vimeo

Partially Non-Autoregressive Image Captioning Proceedings of …

Web10 de oct. de 2024 · The closest work to ours is Masked Non-Autoregressive Image Captioning by Gao et al. [6], which uses. a BERT model as the generator and in volves 2 steps-reﬁnement on the generated sequence ... Web- "Masked Non-Autoregressive Image Captioning" Table 1: Performance comparisons with different evaluation metrics in offline testing. The masking ratio set of MNIC are all {0.4, 0.6, 0.8, 1.0} during training and inference, where 1R and 2R indicate first and second round during inference, respectively. WebFigure 1: Given an image, autoregressive image captioning (AIC) model generates a caption word by word and Non-Autoregressive Image Captioning (NAIC) model … ian toft

All up to You: Controllable Video Captioning with a Masked …

Non-Autoregressive Image Captioning with Counterfactuals

Web18 de may. de 2024 · A partially non-autoregressive model, named PNAIC, is introduced, which considers a caption as a series of concatenated word groups, and is capable of generating accurate captions as well as preventing common incoherent errors. Current state-of-the-art image captioning systems usually generated descriptions … Web10 de may. de 2024 · Figure 1: Given an image, autoregressive image captioning (AIC) model generates a caption word by word, while Non-Autoregressive Image Captioning (NAIC) model outputs all words in parallel. However, existing non-autoregressive models still have a large gap in generation quality compared to their autoregressive … ian to facebookWebFigure 1. Given an image, autoregressive image captioning (AIC) model generates a caption word by word and Non-Autoregressive Image Captioning (NAIC) model … ian tofts

"Webpursuing an improved non-autoregressive sentence genera-tion to accelerate image captioning. We ﬁrst describe the popular image encoder types, then show how we imple-ment a hierarchical decoder which consists of a position alignment and a ﬁne sentence decoder, to realize a non-autoregressive decoding procedure. Finally, we introduce a " - Masked non-autoregressive image captioning

Masked non-autoregressive image captioning

Fast Image Caption Generation with Position Alignment - GitHub …

Web3 de jun. de 2024 · Non-autoregressive decoding has been proposed to tackle slow generation for neural machine translation but suffers from multimodality problem due to … WebTowards Accurate Image Coding: Improved Autoregressive Image Generation with Dynamic Vector Quantization Mengqi Huang · Zhendong Mao · Zhuowei Chen · Yongdong Zhang Binary Latent Diffusion Ze Wang · Jiang Wang · Zicheng Liu · Qiang Qiu Align your Latents: High-Resolution Video Synthesis with Latent Diffusion Models

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Web5 de mar. de 2024 · 1 Introduction Figure 1: Control Stable Diffusion with Canny edge map. The canny edge map is input, and the source image is not used when we generate the images on the right. The outputs are achieved with a default prompt “a high-quality, detailed, and professional image”.This prompt is used in this paper as a default prompt … WebFigure 1: Overview of conventional image captioning, refinement-based image captioning, and our future con-text modeling with causal dynamics calibration from non-autoregressive decoder. Note that the non-autoregressive de-coder is not involved at the inference stage to maintain com-putation efficiency. 1 INTRODUCTION Image …

WebIn this paper, we propose masked non-autoregressive decoding for image captioning to address the problems of autoregressive decoding and non-autoregressive decoding. … WebInteresting Concepts in NLP. 走兔. Exposure Bias [1] （曝光偏差）主要是由NMT模型的训练与测试过程的不一致产生的问题。. NMT为了在训练阶段往往采用ground truth作为context信息进行预测，并使用Cross entropy 作为监督信号（Teacher forcing [2] ）。. 但在实际测试阶段，context信息 ...

Web18 de mar. de 2024 · Partially Non-Autoregressive Image Captioning. In AAAI2024. Zhengcong Fei. Retrieve and Revise: Improving Peptide Identification with Similar Mass … Web10 de may. de 2024 · Most image captioning models are autoregressive, i.e. they generate each word by conditioning on previously generated words, which leads to …

Web18 de may. de 2024 · Current state-of-the-art image captioning systems usually generated descriptions autoregressively, i.e., every forward step conditions on the given image and …

WebMasked Non-Autoregressive Image Captioning Junlong Gao1 Xi Meng2 Shiqi Wang5 Xia Li1 Shanshe Wang3;4 Siwei Ma 3;4Wen Gao 1Peking University Shenzhen Graduate … ian to englishWeb3 de jun. de 2024 · Request PDF Masked Non-Autoregressive Image Captioning Existing captioning models often adopt the encoder-decoder architecture, where the … ian toflerWebFigure 3: Example of ground truth captions, the generated captions of AIC and MNIC using different sequence lengths. - "Masked Non-Autoregressive Image Captioning" Skip to search form Skip to main content Skip to account menu. Semantic Scholar's Logo. Search 206,080,376 papers from all fields of science. Search. Sign ... ian todd microsoftWeb11 de oct. de 2024 · Non-autoregressive method is first proposed by (Gu et al., 2024; Gao et al., 2024a) to address the above issues, allowing the image captioning model to generate all target words simultaneously. NAIC replaces w < t with independent latent variable z to remove the sequential dependencies and rewrite Equation 1 as: ian todd sheffieldWeb27 de nov. de 2024 · Existing state-of-the-art autoregressive video captioning methods (ARVC) generate captions sequentially, which leads to low inference efficiency. … ian todd \\u0026 son plumbing \\u0026 heating limitedWebthe decoding consistency of image captioning, in this paper, we propose a Non-Autoregressive Image Captioning (NA-IC) model with a novel training paradigm: … ian to hit carolinasWebFigure 2: Investigations of the influences of different stages and lengths in terms of SP and CD. - "Masked Non-Autoregressive Image Captioning" Skip to search form Skip to main content Skip to account menu. Semantic Scholar's Logo. Search 209,973,119 papers from all fields of science. Search. Sign ... ian todd the glasgow chronicles