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Masked non-autoregressive image captioning

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 … WebThis repo presents an overview of Non-autoregressive (NAR) models, including links to related papers and corresponding codes. NAR models aim to speed up decoding and reduce the inference latency, then realize better industry application. However, this improvement of speed comes at the expense of the decline of quality.

Adding Conditional Control to Text-to-Image Diffusion Models

Webthe decoding consistency of image captioning, in this paper, we propose a Non-Autoregressive Image Captioning (NA-IC) model with a novel training paradigm: Counterfactuals-critical Multi-Agent Learning (CMAL). Specifically, we con-sider NAIC as a cooperative multi-agent reinforcement learn-ing (MARL) [Bus¸oniu et al., 2010] system, … WebFigure 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 … sjf with arrival time in c https://pkokdesigns.com

Non-Autoregressive Image Captioning with Counterfactuals …

WebFigure 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 ... Web• We propose a partially non-autoregressive model to accel-erate image captioning generation, splitting each caption into a series of word groups. The captioner keeps the au-toregressive property in local but relieves in global. To our knowledge, this is the first work to introduce a partially non-autoregressive paradigm into image captioning. WebFigure 1. Given an image, autoregressive image captioning (AIC) model generates a caption word by word and Non-Autoregressive Image Captioning (NAIC) model … sjfwpt.sphkeyuan.com

Partially Non-Autoregressive Image Captioning

Category:Masked Non-Autoregressive Image Captioning – arXiv Vanity

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Masked non-autoregressive image captioning

[2005.04690] Non-Autoregressive Image Captioning with …

WebMulti-modal Video Chapter Generation. 5. Video title generation and summary generation. 可以的应用场景：. （1）今日头条推送的要文，就是简短title和summary. （2）电商产品提供一些简介。. 一些广告图是没有写 … Web29 de oct. de 2024 · Image caption generation (a.k.a., image captioning), is the task of generating natural language captions for given images.Due to its multimodal nature and numerous downstream applications (e.g., human-machine interaction [], content-based image retrieval [], and assisting visually-impaired people []), caption generation has …

Masked non-autoregressive image captioning

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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 … WebFigure 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 ...

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 … 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 ...

Web13 de dic. de 2024 · Our decoding part consists of a position alignment to order the words that describe the content detected in the given image, and a fine non-autoregressive decoder to generate elegant descriptions. Furthermore, we introduce an inference strategy that regards position information as a latent variable to guide the further sentence … 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 previously produced words. The sequential attribution causes a unavoidable decoding latency. Non-autoregressive image captioning, on the other hand, predicts the entire …

WebIn masked non-autoregressive decoding, we mask several kinds of ratios of the input sequences during training, and generate captions parallelly in several stages from a totally masked sequence to ...

Web4 de nov. de 2024 · Abstract. Controllable video captioning is generating video descriptions following designated control signals. However, most controllable video captioning models focus exclusively on contents of interest or descriptive syntax. In this paper, we propose to guide the video caption generation with a Masked Scene Graph (MSG). suthers school twitterWebInteresting 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 ... suthers school ofstedWeb27 de nov. de 2024 · Existing state-of-the-art autoregressive video captioning methods (ARVC) generate captions sequentially, which leads to low inference efficiency. … suthers school term dates 2023WebNon-autoregressive image captioning with continuous iterative refinement, which eliminates the sequential dependence in a sentence generation, ... criteria with constant steps. In this work, we utilize masked predic-tion [12, 19] as the representation of IR-NAIC due to its excellent performance and simplicity, where tokens are randomly masked in suthers school uniformWebAutoregressive, non-autoregressive, semi-autoregressive image captioning流程示例. 模型框架 方法介绍 作者参考自回归和非自回归的优缺点,提出了一种折中的方法-半自回 … sjf womens lacrosseWebTowards 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 sjf with arrival time program in c++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 … sjf work advice