Convolutional Image Captioning 2018-11-04 20:42:07 Paper: http://openaccess.thecvf.com/content_cvpr_2018/papers/Aneja_Convolutional_Image_Captioning_CVPR_2018_paper.pdf Code: https://github.com/aditya12agd5/convcap Related Papers: 1. Convolutional Se…

Link of the Paper: https://arxiv.org/abs/1711.09151 Motivation: LSTM units are complex and inherently sequential across time. Convolutional networks have shown advantages on machine translation and conditional image generation. Innovation: The author…

Link of the Paper: https://arxiv.org/abs/1705.03122 Motivation: Compared to recurrent layers, convolutions create representations for fixed size contexts, however, the effective context size of the network can easily be made larger by stacking severa…

目录 故事背景 U-Net 具体结构 损失 数据扩充 发表在2015 MICCAI.原本是一篇医学图像分割的论文,但由于U-Net杰出的网络设计,得到了8k+的引用. 摘要 There is large consent that successful training of deep networks requires many thousand annotated training samples. In this paper, we present a network and trainin…

今天给大家带来一篇来自CVPR 2017关于人脸识别的文章. 文章题目:Deep Convolutional Neural Network using Triplets of Faces, Deep Ensemble, and 摘要: 文章动机:人脸识别在一个没有约束的环境下,在计算机视觉中是一个非常有挑战性的问题.同一个身份的人脸当呈现不同的装饰,不同的姿势和不同的表情都可以使人脸看起来完全不同.这种相同身份的变化可以压倒不同身份的变化,这样给人脸识别带来更大的挑战,特别是在没有约束的环境下.…

目录 故事背景 建模现实噪声 CBDNet 非对称损失 数据库 实验 发表在2019 CVPR. 摘要 While deep convolutional neural networks (CNNs) have achieved impressive success in image denoising with additive white Gaussian noise (AWGN), their performance remains limited on real-world noisy p…

目录 摘要 故事要点 模型训练 发表在2018年CVPR. 以下对于一些专业术语的翻译可能有些问题. 摘要 有损压缩是一个优化问题,其优化目标是率失真,优化对象是编码器.量化器和解码器(同时优化). Lossy image compression can be formulated as a joint rate-distortion optimization to learn encoder, quantizer, and decoder. 其中,量化器和离散熵预测(discrete entr…

Papers Published in 2018 Convolutional Image Captioning - Jyoti Aneja et al., CVPR 2018 - [ Paper Reading ] Learning to Evaluate Image Captioning - Yin Cui et al., CVPR 2018 - [ Paper Reading ] CNN+CNN: Convolutional Decoders for Image Captioning - Q…

Image Caption: Automatically describing the content of an image domain:CV+NLP Category:(by myself, you can read the survey for detail.) CNN+RNN, with attention mechanisms Reinforcement Learning GAN Compositional Architecture: Review Network, Guiding…

Awesome Image Captioning 2018-12-03 19:19:56 From: https://github.com/zhjohnchan/awesome-image-captioning Papers 2010 I2t: Image parsing to text description - Yao B Z et al, P IEEE 2011. 2011 Im2Text: Describing Images Using 1 Million Captioned Photo…