arXiv每日推荐-3.22:计算机视觉/图像处理每日论文速递

同步公众号(arXiv每日学术速递)

[检测分类相关]:
【1】 JAA-Net: Joint Facial Action Unit Detection and Face Alignment via Adaptive Attention
JAA-Net:通过自适应注意的联合面部动作单元检测和人脸对齐
作者: Zhiwen Shao, Lizhuang Ma
链接:https://arxiv.org/abs/2003.08834

【2】 Brain MRI-based 3D Convolutional Neural Networks for Classification of Schizophrenia and Controls
基于脑MRI的3D卷积神经网络用于精神分裂症和对照组的分类
作者: Mengjiao Hu, Cuntai Guan
链接:https://arxiv.org/abs/2003.08818

【3】 Deep Object Detection based Mitosis Analysis in Breast Cancer Histopathological Images
基于深层目标检测的乳腺癌组织病理学图像有丝分裂分析
作者: Anabia Sohail, Saranjam Khan
备注:Tables: 4, Figures 11, Pages: 21
链接:https://arxiv.org/abs/2003.08803

【4】 Pedestrian Detection: The Elephant In The Room
行人检测:房间里的大象
作者: Irtiza Hasan, Ling Shao
链接:https://arxiv.org/abs/2003.08799

【5】 Incremental Object Detection via Meta-Learning
基于元学习的增量目标检测
作者: K J Joseph, Ling Shao
链接:https://arxiv.org/abs/2003.08798

【6】 Teacher-Student chain for efficient semi-supervised histology image classification
用于有效半监督组织学图像分类的教师-学生链
作者: Shayne Shaw, Alison Q O’Neil
备注:AI for Affordable Healthcare workshop at ICLR 2020
链接:https://arxiv.org/abs/2003.08797

【7】 Deep Active Learning for Remote Sensing Object Detection
用于遥感目标检测的深度主动学习
作者: Zhenshen Qu, Pengbo Zhao
链接:https://arxiv.org/abs/2003.08793

【8】 Self-Guided Adaptation: Progressive Representation Alignment for Domain Adaptive Object Detection
自引导自适应:用于域自适应目标检测的渐进式表示对齐
作者: Zongxian Li, Yonghong Tian
链接:https://arxiv.org/abs/2003.08777

【9】 “Who is Driving around Me?” Unique Vehicle Instance Classification using Deep Neural Features
"谁在我身边开车?"使用深度神经特征的唯一车辆实例分类
作者: Tim Oosterhuis, Lambert Schomaker
链接:https://arxiv.org/abs/2003.08771

【10】 ElixirNet: Relation-aware Network Architecture Adaptation for Medical Lesion Detection
ElixirNet:用于医疗病变检测的关系感知网络体系结构自适应
作者: Chenhan Jiang, Nong Xiao
备注:7 pages, 5 figure, AAAI2020
链接:https://arxiv.org/abs/2003.08770

【11】 Dense Crowds Detection and Surveillance with Drones using Density Maps
使用密度地图的无人机对密集人群的检测和监视
作者: Javier Gonzalez-Trejo, Diego Mercado-Ravell
链接:https://arxiv.org/abs/2003.08766

【12】 Unique Class Group Based Multi-Label Balancing Optimizer for Action Unit Detection
基于唯一类组的多标签平衡优化器用于动作单元检测
作者: Ines Rieger, Dominik Seuss
备注:Accepted at the 15th IEEE International Conference on Automatic Face and Gesture Recognition 2020, Workshop “Affect Recognition in-the-wild: Uni/Multi-Modal Analysis & VA-AU-Expression Challenges”. arXiv admin note: substantial text overlap with arXiv:2002.03238
链接:https://arxiv.org/abs/2003.08751

【13】 Out-of-Distribution Detection in Multi-Label Datasets using Latent Space of β β -VAE
使用 β β -vae潜在空间的多标签数据集中的分布外检测
作者: Vijaya Kumar Sundar, Abhishek Dubey
备注:Workshop on Assured Autonomy (WAAS) -2020
链接:https://arxiv.org/abs/2003.08740

【14】 Fast Distance-based Anomaly Detection in Images Using an Inception-like Autoencoder
基于距离的快速图像异常检测
作者: Natasa Sarafijanovic-Djukic, Jesse Davis
备注:22nd International Conference on Discovery Science, DS 2019
链接:https://arxiv.org/abs/2003.08731

【15】 Leveraging Frequency Analysis for Deep Fake Image Recognition
利用频率分析进行深度伪图像识别
作者: Joel Frank, Thorsten Holz
链接:https://arxiv.org/abs/2003.08685

【16】 Detecting Deepfakes with Metric Learning
利用度量学习检测深度伪造
作者: Akash Kumar, Arnav Bhavsar
链接:https://arxiv.org/abs/2003.08645

【17】 Depth Potentiality-Aware Gated Attention Network for RGB-D Salient Object Detection
深度电位感知的门控注意网络在RGB-D凸起目标检测中的应用
作者: Zuyao Chen, Qingming Huang
链接:https://arxiv.org/abs/2003.08608

【18】 Detecting Lane and Road Markings at A Distance with Perspective Transformer Layers
用透视变压器层检测远处的车道和道路标记
作者: Zhuoping Yu, Junqiao Zhao
链接:https://arxiv.org/abs/2003.08550

【19】 Evaluating Salient Object Detection in Natural Images with Multiple Objects having Multi-level Saliency
具有多级显著性的多目标自然图像中凸起目标检测的评价
作者: Gökhan Yildirim, Sabine Süsstrunk
链接:https://arxiv.org/abs/2003.08514

【20】 Detecting Pancreatic Adenocarcinoma in Multi-phase CT Scans via Alignment Ensemble
对齐集合在多期CT扫描中检测胰腺癌的研究
作者: Yingda Xia, Alan L. Yuille
链接:https://arxiv.org/abs/2003.08441

【21】 Synthesize then Compare: Detecting Failures and Anomalies for Semantic Segmentation
合成然后比较:为语义分割检测故障和异常
作者: Yingda Xia, Alan Yuille
链接:https://arxiv.org/abs/2003.08440

【22】 Overinterpretation reveals image classification model pathologies
过度解读揭示图像分类模型病理
作者: Brandon Carter, David Gifford
链接:https://arxiv.org/abs/2003.08907

【23】 Extremal Region Analysis based Deep Learning Framework for Detecting Defects
基于极值区域分析的缺陷检测深度学习框架
作者: Zelin Deng, Colleen P. Bailey
链接:https://arxiv.org/abs/2003.0852

[其他]
【1】 A Matlab Toolbox for Feature Importance Ranking
特征重要性排序的Matlab工具箱
作者: Shaode Yu, Yaoqin Xie
链接:https://arxiv.org/abs/2003.0873

【2】 Addressing the Memory Bottleneck in AI Model Training
解决AI模型训练中的内存瓶颈问题
作者: David Ojika, Prashant Shah
备注:Presented at Workshop on MLOps Systems at MLSys 2020 Conference, Austin TX
链接:https://arxiv.org/abs/2003.0873

更多文章参考原文:https://zhuanlan.zhihu.com/p/114655178

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