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计算机视觉每日论文速递[08.23]

计算机视觉每日论文速递[08.23]

作者: arXiv每日论文速递 | 来源:发表于2019-08-24 13:49 被阅读22次

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    cs.CV 方向,今日共计39篇

    [检测分类相关]:

    【1】 EGNet:Edge Guidance Network for Salient Object Detection
    EGNet:用于凸起目标检测的边缘引导网络
    作者: Jia-Xing Zhao, Ming-Ming Cheng
    链接:https://arxiv.org/abs/1908.08297

    【2】 Object detection on aerial imagery using CenterNet
    基于Centernet的航空影像目标检测
    作者: Dheeraj Reddy Pailla, Sai Saketh Chennamsetty
    链接:https://arxiv.org/abs/1908.08244

    【3】 Multi-Stream Single Shot Spatial-Temporal Action Detection
    多流单镜头时空动作检测
    作者: Pengfei Zhang, Benyuan Liu
    链接:https://arxiv.org/abs/1908.08178

    【4】 Multiple instance dense connected convolution neural network for aerial image scene classification
    航空影像场景分类的多实例稠密连接卷积神经网络
    作者: Qi Bi, Kai Xu
    备注:5 pages,3 figures, a conference paper accepted by IEEE ICIP 2019
    链接:https://arxiv.org/abs/1908.08156

    【5】 Contour Detection in Cassini ISS images based on Hierarchical Extreme Learning Machine and Dense Conditional Random Field
    基于分层极值学习机和稠密条件随机场的卡西尼ISS图像轮廓检测
    作者: Xiqi Yang, Zhan Li
    链接:https://arxiv.org/abs/1908.08279

    【6】 A CNN toolbox for skin cancer classification
    CNN皮肤癌分类工具箱
    作者: Fabrizio Nunnari, Daniel Sonntag
    链接:https://arxiv.org/abs/1908.08187

    【7】 Building change detection based on multi-scale filtering and grid partition
    基于多尺度滤波和网格划分的建筑物变化检测
    作者: Qi Bi, Kai Xu
    链接:https://arxiv.org/abs/1908.08164

    【8】 Transferability and Hardness of Supervised Classification Tasks
    监督分类任务的可移植性和硬度
    作者: Anh T. Tran, Tal Hassner
    备注:This paper is published at the International Conference on Computer Vision (ICCV) 2019
    链接:https://arxiv.org/abs/1908.08142

    [分割/语义相关]:

    【1】 Uncertainty-Guided Domain Alignment for Layer Segmentation in OCT Images
    不确定导引的OCT图像层分割区域对齐方法
    作者: Jiexiang Wang, Yefeng Zheng
    链接:https://arxiv.org/abs/1908.08242

    【2】 Optimal input configuration of dynamic contrast enhanced MRI in convolutional neural networks for liver segmentation
    用于肝脏分割的卷积神经网络动态增强MRI的最优输入配置
    作者: Mariëlle J.A. Jansen, Josien P.W. Pluim
    备注:Submitted to SPIE Medical Imaging 2019
    链接:https://arxiv.org/abs/1908.08251

    【3】 Boundary Aware Networks for Medical Image Segmentation
    边界感知网络在医学图像分割中的应用
    作者: Ali Hatamizadeh, Andriy Myronenko
    备注:Accepted to Machine Learning in Medical Imaging (MLMI 2019)
    链接:https://arxiv.org/abs/1908.08071

    【4】 More unlabelled data or label more data? A study on semi-supervised laparoscopic image segmentation
    更多未标记的数据或标记更多数据?半监督腹腔镜图像分割的研究
    作者: Yunguan Fu, Yipeng Hu
    备注:Accepted to MICCAI MIL3ID 2019
    链接:https://arxiv.org/abs/1908.08035

    [GAN/对抗式/生成式相关]:

    【1】 Adversarial-Based Knowledge Distillation for Multi-Model Ensemble and Noisy Data Refinement
    基于对抗性的多模型集成和噪声数据精化的知识提取
    作者: Zhiqiang Shen, Marios Savvides
    备注:This is an extended version of our previous conference paper arXiv:1812.02425
    链接:https://arxiv.org/abs/1908.08520

    【2】 Saliency Methods for Explaining Adversarial Attacks
    解释对抗攻击的显着性方法
    作者: Jindong Gu, Volker Tresp
    链接:https://arxiv.org/abs/1908.08413

    [行为/时空/光流/姿态/运动]:
    【1】 Predicting Animation Skeletons for 3D Articulated Models via Volumetric Nets
    基于体积网的3D关节模型动画骨架预测
    作者: Zhan Xu, Karan Singh
    备注:3DV 2019
    链接:https://arxiv.org/abs/1908.08506

    【2】 Trajectory Space Factorization for Deep Video-Based 3D Human Pose Estimation
    基于深度视频的三维人体姿态估计的轨迹空间分解
    作者: Jiahao Lin, Gim Hee Lee
    备注:13 pages, 5 figures. Accepted in BMVC 2019
    链接:https://arxiv.org/abs/1908.08289

    【3】 Pro-Cam SSfM: Projector-Camera System for Structure and Spectral Reflectance from Motion
    Pro-CAM SSFM:用于结构和光谱反射比的投影仪-摄像机系统
    作者: Chunyu Li, Masatoshi Okutomi
    备注:Accepted by ICCV 2019. Project homepage: this http URL
    链接:https://arxiv.org/abs/1908.08185

    【4】 Motion correction of dynamic contrast enhanced MRI of the liver
    肝脏动态增强MRI的运动校正
    作者: Mariëlle J.A. Jansen, Josien P.W. Pluim
    链接:https://arxiv.org/abs/1908.08254

    [半/弱/无监督相关]:
    【1】 3C-Net: Category Count and Center Loss for Weakly-Supervised Action Localization
    3C-NET:弱监督操作定位的类别计数和中心损失
    作者: Sanath Narayan, Ling Shao
    备注:To appear in ICCV 2019
    链接:https://arxiv.org/abs/1908.08216

    [视频理解VQA/caption等]:
    【1】 Sequential Latent Spaces for Modeling the Intention During Diverse Image Captioning
    用于不同图像字幕中意图建模的顺序潜在空间
    作者: Jyoti Aneja, Alexander Schwing
    备注:Accepted to ICCV 2019
    链接:https://arxiv.org/abs/1908.08529

    [超分辨率]:
    【1】 Progressive Face Super-Resolution via Attention to Facial Landmark
    通过关注人脸地标的渐进式人脸超分辨率
    作者: Deokyun Kim, Dae-Shik Kim
    备注:BMVC 2019 Accepted
    链接:https://arxiv.org/abs/1908.08239

    [点云]:
    【1】 Globally optimal registration of noisy point clouds
    噪声点云的全局最优配准
    作者: Rangaprasad Arun Srivatsan, Howie Choset
    链接:https://arxiv.org/abs/1908.08162

    [深度depth相关]:
    【1】 Indoor Depth Completion with Boundary Consistency and Self-Attention
    具有边界一致性和自我关注的室内深度完成
    作者: Yu-Kai Huang, Winston H. Hsu
    备注:Accepted by RLQ2019 @ ICCV 2019
    链接:https://arxiv.org/abs/1908.08344

    [人脸相关]:
    【1】 Scoot: A Perceptual Metric for Facial Sketches
    SCOOT:面部草图的感知度量
    作者: Deng-Ping Fan, Rongrong Ji
    备注:Code & dataset:this http URL, 11 pages, ICCV 2019, First one good evaluation metric for facial sketh that consistent with human judgment. arXiv admin note: text overlap with arXiv:1804.02975
    链接:https://arxiv.org/abs/1908.08433

    [其他视频相关]:
    【1】 Compositional Video Prediction
    合成视频预测
    作者: Yufei Ye, Shubham Tulsiani
    备注:accepted to ICCV19
    链接:https://arxiv.org/abs/1908.08522

    [其他]:
    【1】 VL-BERT: Pre-training of Generic Visual-Linguistic Representations
    VL-BERT:类属视觉语言表征的预训练
    作者: Weijie Su, Jifeng Dai
    链接:https://arxiv.org/abs/1908.08530

    【2】 ViCo: Word Embeddings from Visual Co-occurrences
    VICO:来自视觉共现的单词嵌入
    作者: Tanmay Gupta, Derek Hoiem
    备注:Accepted to ICCV 2019. Project Page: this http URL
    链接:https://arxiv.org/abs/1908.08527

    【3】 EPIC-Fusion: Audio-Visual Temporal Binding for Egocentric Action Recognition
    EPIC-Fusion:用于自我中心行为识别的视听时间绑定
    作者: Evangelos Kazakos, Dima Damen
    备注:Accepted for presentation at ICCV 2019
    链接:https://arxiv.org/abs/1908.08498

    【4】 Noise Flow: Noise Modeling with Conditional Normalizing Flows
    噪声流:使用条件归一化流的噪声建模
    作者: Abdelrahman Abdelhamed, Michael S. Brown
    链接:https://arxiv.org/abs/1908.08453

    【5】 Deep Green Function Convolution for Improving Saliency in Convolutional Neural Networks
    改进卷积神经网络显着性的深层格林函数卷积
    作者: Dominique Beaini, Maxime Raison
    链接:https://arxiv.org/abs/1908.08331

    【6】 Mask TextSpotter: An End-to-End Trainable Neural Network for Spotting Text with Arbitrary Shapes
    mask TextSpotter:一个端到端可训练的神经网络用于任意形状的文本识别
    作者: Minghui Liao, Xiang Bai
    链接:https://arxiv.org/abs/1908.08207

    【7】 U-Net Training with Instance-Layer Normalization
    具有实例层规范化的U-NET训练
    作者: Xiao-Yun Zhou, Guang-Zhong Yang
    备注:8 pages, 3 figures, accepted by MICCAI-MMMI 2019 workshop
    链接:https://arxiv.org/abs/1908.08466

    【8】 Improved MR to CT synthesis for PET/MR attenuation correction using Imitation Learning
    利用模仿学习改进的用于PET/MR衰减校正的MR to CT合成
    作者: Kerstin Kläser, Sebastien Ourselin
    备注:Aceppted at SASHIMI2019
    链接:https://arxiv.org/abs/1908.08431

    【9】 Image Colorization By Capsule Networks
    基于胶囊网络的图像着色
    作者: Gökhan Özbulak
    备注:Accepted to New Trends in Image Restoration and Enhancement(NTIRE) Workshop at CVPR 2019
    链接:https://arxiv.org/abs/1908.08307

    【10】 NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations
    NL-LinkNet:通过非本地操作实现更轻但更精确的道路提取
    作者: Yooseung Wang, Taegyun Jeon
    链接:https://arxiv.org/abs/1908.08223

    【11】 BIM-assisted object recognition for the on-site autonomous robotic assembly of discrete structures
    BIM辅助的离散结构现场自主机器人装配对象识别
    作者: Mohamed Dawod, Sean Hanna
    链接:https://arxiv.org/abs/1908.08209

    【12】 An Image Fusion Scheme for Single-Shot High Dynamic Range Imaging with Spatially Varying Exposures
    一种用于空间变化曝光的单次激发高动态范围成像的图像融合方案
    作者: Chihiro Go, Hitoshi Kiya
    链接:https://arxiv.org/abs/1908.08195

    【13】 DUAL-GLOW: Conditional Flow-Based Generative Model for Modality Transfer
    双辉光:基于条件流的模态转换生成模型
    作者: Haoliang Sun, Vikas Singh
    链接:https://arxiv.org/abs/1908.08074

    【14】 InSituNet: Deep Image Synthesis for Parameter Space Exploration of Ensemble Simulations
    InSituNet:用于集成仿真参数空间探索的深度图像合成
    作者: Wenbin He, Tom Peterka
    链接:https://arxiv.org/abs/1908.00407

    翻译:腾讯翻译君

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