计算机视觉学术速递[2021.7.28]

arxivdaily.com 公众号:arXiv每日学术速递

转载自 https://zhuanlan.zhihu.com/p/393835899

Transformer(2篇)

【1】 Exploring Sequence Feature Alignment for Domain Adaptive Detection Transformers
标题：基于域自适应检测Transformer的序列特征比对研究
作者：Wen Wang,Yang Cao,Jing Zhang,Fengxiang He,Zheng-Jun Zha,Yonggang Wen,Dacheng Tao
机构： University of Science and Technology of China, Institute of Artificial Intelligence, Hefei Comprehensive National Science Center
备注：Accepted by ACM MM2021. Source code is available at: this https URL
链接：https://arxiv.org/abs/2107.12636

【2】 PiSLTRc: Position-informed Sign Language Transformer with Content-aware Convolution
标题：PiSLTRc：带内容感知卷积的位置知晓手语转换器
作者：Pan Xie,Mengyi Zhao,Xiaohui Hu
机构： directly learning thePan Xie and Mengyi Zhao are with the School of Automation Science andElectrical Engineering, Beihang University
链接：https://arxiv.org/abs/2107.12600

检测相关(11篇)

【1】 Real-time Keypoints Detection for Autonomous Recovery of the Unmanned Ground Vehicle
标题：无人地面车辆自主回收的实时关键点检测
作者：Jie Li,Sheng Zhang,Kai Han,Xia Yuan,Chunxia Zhao,Yu Liu
备注：IET Image Processing, code: this https URL
链接：https://arxiv.org/abs/2107.12852

【2】 Clickbait Detection in YouTube Videos
标题：YouTube视频中的点击诱饵检测
作者：Ruchira Gothankar,Fabio Di Troia,Mark Stamp
链接：https://arxiv.org/abs/2107.12791

【3】 Discriminative-Generative Representation Learning for One-Class Anomaly Detection
标题：一类异常检测的判别-生成表示学习
作者：Xuan Xia,Xizhou Pan,Xing He,Jingfei Zhang,Ning Ding,Lin Ma
机构：Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen , P. R. China., Institute of Robotics and Intelligent Manufacturing, Chinese University of Hong Kong, Shenzhen, P. R. China., ∗Corresponding author.
备注：e.g.:13 pages, 6 figures
链接：https://arxiv.org/abs/2107.12753

【4】 DV-Det: Efficient 3D Point Cloud Object Detection with Dynamic Voxelization
标题：DV-DET：基于动态体素化的高效三维点云目标检测
作者：Zhaoyu Su,Pin Siang Tan,Yu-Hsing Wang
机构：DESR Laboratory, Department of Civil and Environmental Engineering, Hong Kong University of Science and Technology
链接：https://arxiv.org/abs/2107.12707

【5】 Dynamic and Static Object Detection Considering Fusion Regions and Point-wise Features
标题：融合区域和逐点特征的动态静电目标检测
作者：Andrés Gómez,Thomas Genevois,Jerome Lussereau,Christian Laugier
备注：6 pages, 7 figures
链接：https://arxiv.org/abs/2107.12692

【6】 Adaptive Boundary Proposal Network for Arbitrary Shape Text Detection
标题：用于任意形状文本检测的自适应边界建议网络
作者：Shi-Xue Zhang,Xiaobin Zhu,Chun Yang,Hongfa Wang,Xu-Cheng Yin
机构：School of Computer and Communication Engineering, University of Science and Technology Beijing, USTB-EEasyTech Joint Lab of Artificial Intelligence, Tencent Technology (Shenzhen) Co., Ltd
备注：None
链接：https://arxiv.org/abs/2107.12664

【7】 Unsupervised Outlier Detection using Memory and Contrastive Learning
标题：基于记忆和对比学习的无监督孤立点检测
作者：Ning Huyan,Dou Quan,Xiangrong Zhang,Xuefeng Liang,Jocelyn Chanussot,Licheng Jiao
机构：School of Artificial Intelligence, Xidian University, Shaanxi, China, Research center of Inria Grenoble-Rhone-Alpes, France
链接：https://arxiv.org/abs/2107.12642

【8】 CFLOW-AD: Real-Time Unsupervised Anomaly Detection with Localization via Conditional Normalizing Flows
标题：CFLOW-AD：基于条件归一化流定位的实时无监督异常检测
作者：Denis Gudovskiy,Shun Ishizaka,Kazuki Kozuka
机构：Panasonic AI Lab, USA, Panasonic Technology Division, Japan
备注：Accepted to WACV 2022. Preprint
链接：https://arxiv.org/abs/2107.12571

【9】 Parallel Detection for Efficient Video Analytics at the Edge
标题：一种高效边缘视频分析的并行检测方法
作者：Yanzhao Wu,Ling Liu,Ramana Kompella
机构：School of Computer Science, Georgia Institute of Technology, Atlanta, Georgia, Cisco Systems, Inc., West Tasman Dr., San Jose, California
链接：https://arxiv.org/abs/2107.12563

【10】 Perception-and-Regulation Network for Salient Object Detection
标题：感知调节网络在醒目目标检测中的应用
作者：Jinchao Zhu,Xiaoyu Zhang,Xian Fang,Junnan Liu
机构： NankaiUniversity, Nankai University, Harbin Engineering University
链接：https://arxiv.org/abs/2107.12560

【11】 Optimizing Operating Points for High Performance Lesion Detection and Segmentation Using Lesion Size Reweighting
标题：基于病灶大小加权的高性能病变检测与分割操作点优化
作者：Brennan Nichyporuk,Justin Szeto,Douglas L. Arnold,Tal Arbel
机构： Centre for Intelligent Machines, McGill University, Montreal, Canada, MILA (Quebec Artificial Intelligence Institute), McGill University, Montreal, Canada, Montreal Neurological Institute, McGill University, Montreal, Canada
备注：Accepted at MIDL 2021
链接：https://arxiv.org/abs/2107.12978

分类|识别相关(5篇)

【1】 Multi-Scale Local-Temporal Similarity Fusion for Continuous Sign Language Recognition
标题：用于连续手语识别的多尺度局域-时态相似度融合
作者：Pan Xie,Zhi Cui,Yao Du,Mengyi Zhao,Jianwei Cui,Bin Wang,Xiaohui Hu
机构：Huc, Beihang University, Beijing, China, Xiaomi AI Lab, Beijing, China, Institute of Software, Chinese Academy of Sciences, Beijing, China
链接：https://arxiv.org/abs/2107.12762

【2】 Real-Time Activity Recognition and Intention Recognition Using a Vision-based Embedded System
标题：基于视觉的嵌入式系统实时行为识别和意图识别
作者：Sahar Darafsh,Saeed Shiry Ghidary,Morteza Saheb Zamani
机构：Computer Engineering Department, Amirkabir University of Technology, Tehran, Iran, Mathematics and Computer Science Department
链接：https://arxiv.org/abs/2107.12744

【3】 ENHANCE (ENriching Health data by ANnotations of Crowd and Experts): A case study for skin lesion classification
标题：增强(通过人群和专家的注释丰富健康数据)：皮肤病变分类的案例研究
作者：Ralf Raumanns,Gerard Schouten,Max Joosten,Josien P. W. Pluim,Veronika Cheplygina
机构： Fontys University of Applied Science, Eindhoven, The Netherlands, Eindhoven University of Technology, Eindhoven, The Netherlands, IT University of Copenhagen, Denmark
链接：https://arxiv.org/abs/2107.12734

【4】 Feature Fusion Methods for Indexing and Retrieval of Biometric Data: Application to Face Recognition with Privacy Protection
标题：生物特征数据索引与检索的特征融合方法及其在隐私保护人脸识别中的应用
作者：Pawel Drozdowski,Fabian Stockhardt,Christian Rathgeb,Dailé Osorio-Roig,Christoph Busch
机构：dasec – Biometrics and Internet Security Research Group, Hochschule Darmstadt, Germany
链接：https://arxiv.org/abs/2107.12675

【5】 Semantically Self-Aligned Network for Text-to-Image Part-aware Person Re-identification
标题：基于语义自对齐网络的文本到图像部分感知人物再识别
作者：Zefeng Ding,Changxing Ding,Zhiyin Shao,Dacheng Tao
机构： South China University of Technology, Pazhou Lab, Guangzhou, JD Explore Academy
备注：A new database is provided. Code will be released
链接：https://arxiv.org/abs/2107.12666

分割|语义相关(7篇)

【1】 Remember What You have drawn: Semantic Image Manipulation with Memory
标题：记住您所画的：使用记忆进行语义图像操作
作者：Xiangxi Shi,Zhonghua Wu,Guosheng Lin,Jianfei Cai,Shafiq Joty
机构：Electrical Engineering and Computer, Oregon state university, School of Computer Science and, Nanyang Technological University, Department of Data Science & AI, Monash University
链接：https://arxiv.org/abs/2107.12579

【2】 Self-Supervised Video Object Segmentation by Motion-Aware Mask Propagation
标题：基于运动感知掩模传播的自监督视频对象分割
作者：Bo Miao,Mohammed Bennamoun,Yongsheng Gao,Ajmal Mian
机构：The University of Western Australia, Griffith University
备注：10 pages, 5 figures
链接：https://arxiv.org/abs/2107.12569

【3】 Segmentation in Style: Unsupervised Semantic Image Segmentation with Stylegan and CLIP
标题：风格分割：基于Stylegan和CLIP的无监督语义图像分割
作者：Daniil Pakhomov,Sanchit Hira,Narayani Wagle,Kemar E. Green,Nassir Navab
机构：Johns Hopkins University
链接：https://arxiv.org/abs/2107.12518

【4】 A Comprehensive Study on Colorectal Polyp Segmentation with ResUNet++, Conditional Random Field and Test-Time Augmentation
标题：Resunet++、条件随机场和测试时间增强在大肠息肉分割中的综合研究
作者：Debesh Jha,Pia H. Smedsrud,Dag Johansen,Thomas de Lange,Håvard D. Johansen,Pål Halvorsen,Michael A. Riegler
机构：UiT The Arctic University of Norway, University of Oslo, OsloMetropolitan University, Sahlgrenska University Hospital
备注：Accepted at IEEE Journal of BioMedical and Health Informatics
链接：https://arxiv.org/abs/2107.12435

【5】 Improved-Mask R-CNN: Towards an Accurate Generic MSK MRI instance segmentation platform (Data from the Osteoarthritis Initiative)
标题：改进的Mask R-CNN：迈向准确的通用MSK MRI实例分割平台(来自骨关节炎计划的数据)
作者：Banafshe Felfeliyan,Abhilash Hareendranathan,Gregor Kuntze,Jacob L. Jaremko,Janet L. Ronsky
机构：Ronsky , Affiliations, Schulich School of Engineering, University of Calgary, McCaig Institute for Bone and Joint Health University of Calgary, Calgary, Department of Radiology & Diagnostic Imaging, University of Alberta
链接：https://arxiv.org/abs/2107.12889

【6】 A persistent homology-based topological loss for CNN-based multi-class segmentation of CMR
标题：一种基于持久同调的基于CNN的CMR多类分割拓扑损失
作者：Nick Byrne,James R Clough,Isra Valverde,Giovanni Montana,Andrew P King
机构：a Medical Physics, Guy’s and St. Thomas’ NHS Foundation Trust, London, UK, b School of Biomedical Engineering & Imaging Sciences, King’s College London, UK, c Paediatric Cardiology, Evelina London Children’s Hospital, UK
链接：https://arxiv.org/abs/2107.12689

【7】 Sharp U-Net: Depthwise Convolutional Network for Biomedical Image Segmentation
标题：Sharp U-Net：生物医学图像分割的深度卷积网络
作者：Hasib Zunair,A. Ben Hamza
机构：Concordia Institute for Information Systems Engineering, Concordia University, Montreal, QC, Canada
链接：https://arxiv.org/abs/2107.12461

Zero/Few Shot|迁移|域适配|自适应(5篇)

【1】 A Physiologically-adapted Gold Standard for Arousal During a Stress Induced Scenario
标题：在应激诱导情景中生理适应的唤醒黄金标准
作者：Alice Baird,Lukas Stappen,Lukas Christ,Lea Schumann,Eva-Maria Meßner,Björn W. Schuller
机构：Chair EIHW, University of Augsburg, Augsburg, Germany, KPP, University of Ulm, Ulm, Germany, GLAM, Imperial College London, London, United Kingdom
链接：https://arxiv.org/abs/2107.12964

【2】 Coarse to Fine: Domain Adaptive Crowd Counting via Adversarial Scoring Network
标题：从粗到精：基于对抗性计分网络的领域自适应人群计数
作者：Zhikang Zou,Xiaoye Qu,Pan Zhou,Shuangjie Xu,Xiaoqing Ye,Wenhao Wu,Jin Ye
机构：The Hubei Engineering Research, Center on Big Data Security, School, of Cyber Science and Engineering, Huazhong University of Science and, & Department of Computer Vision, Technology (VIS), Baidu Inc., China, Department of Computer Science and
备注：Accepted by ACMMM2021
链接：https://arxiv.org/abs/2107.12858

【3】 Adaptive Denoising via GainTuning
标题：基于GainTuning的自适应去噪
作者：Sreyas Mohan,Joshua L. Vincent,Ramon Manzorro,Peter A. Crozier,Eero P. Simoncelli,Carlos Fernandez-Granda
机构：Center For Data Science, NYU, School for Engineering of Matter, Transport and Energy, ASU, Center for Neural Science, NYU and Flatiron Institute, Simons Foundation, Courant Institute of Mathematical Sciences, NYU
链接：https://arxiv.org/abs/2107.12815

【4】 Nearest Neighborhood-Based Deep Clustering for Source Data-absent Unsupervised Domain Adaptation
标题：基于最近邻域的源数据无监督域自适应深度聚类
作者：Song Tang,Yan Yang,Zhiyuan Ma,Norman Hendrich,Fanyu Zeng,Shuzhi Sam Ge,Changshui Zhang,Jianwei Zhang
机构： University ofShanghai for Science and Technology, ChinaZhiyuan Ma are with the Institute of Machine Intelligence
链接：https://arxiv.org/abs/2107.12585

【5】 H3D-Net: Few-Shot High-Fidelity 3D Head Reconstruction
标题：H3D-NET：Few-Shot高保真三维头部重建
作者：Eduard Ramon,Gil Triginer,Janna Escur,Albert Pumarola,Jaime Garcia,Xavier Giro-i-Nieto,Francesc Moreno-Noguer
机构：Crisalix SA, Universitat Politecnica de Catalunya, Institut de Robotica i Informatica Industrial, CSIC-UPC, crisalixsa.github.ioh,d-net
链接：https://arxiv.org/abs/2107.12512

半弱无监督|主动学习|不确定性(3篇)

【1】 Energy-Based Open-World Uncertainty Modeling for Confidence Calibration
标题：基于能量的开放世界不确定性建模的置信度校正
作者：Yezhen Wang,Bo Li,Tong Che,Kaiyang Zhou,Dongsheng Li,Ziwei Liu
机构：Microsoft Research Asia, MILA, S-Lab, Nanyang Technological University
备注：ICCV 2021 (Poster)
链接：https://arxiv.org/abs/2107.12628

【2】 Cross-modal Consensus Network for Weakly Supervised Temporal Action Localization
标题：基于跨模态共识网络的弱监督时间动作定位
作者：Fa-Ting Hong,Jia-Chang Feng,Dan Xu,Ying Shan,Wei-Shi Zheng
机构：School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China, Peng Cheng Laboratory, Shenzhen, China, Applied Research Center (ARC), Tencent PCG, Shenzhen, China
备注：ACM International Conference on Multimedia, 2021
链接：https://arxiv.org/abs/2107.12589

【3】 MonoIndoor: Towards Good Practice of Self-Supervised Monocular Depth Estimation for Indoor Environments
标题：单目室内：室内环境自监督单目深度估计的良好实践
作者：Pan Ji,Runze Li,Bir Bhanu,Yi Xu
机构：OPPO US Research Center, InnoPeak Technology, Inc., University of California Riverside
备注：Accepted to ICCV 2021
链接：https://arxiv.org/abs/2107.12429

时序|行为识别|姿态|视频|运动估计(3篇)

【1】 Enriching Local and Global Contexts for Temporal Action Localization
标题：为时态动作本地化丰富局部和全局上下文
作者：Zixin Zhu,Wei Tang,Le Wang,Nanning Zheng,Gang Hua
机构：Xi’an Jiaotong University, University of Illinois at Chicago, Wormpex AI Research
备注：Accepted by ICCV 2021
链接：https://arxiv.org/abs/2107.12960

【2】 Transferable Knowledge-Based Multi-Granularity Aggregation Network for Temporal Action Localization: Submission to ActivityNet Challenge 2021
标题：基于可转移知识的多粒度聚合网络时间动作本地化：从深渊翻滚到ActivityNet挑战赛2021年
作者：Haisheng Su,Peiqin Zhuang,Yukun Li,Dongliang Wang,Weihao Gan,Wei Wu,Yu Qiao
机构：SenseTime Research, SIAT-SenseTime Joint Lab, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shanghai AI Laboratory, Shanghai, China
备注：Winner of HACS21 Challenge Weakly Supervised Learning Track with extra data. arXiv admin note: text overlap with arXiv:2103.13141
链接：https://arxiv.org/abs/2107.12618

【3】 Disentangled Implicit Shape and Pose Learning for Scalable 6D Pose Estimation
标题：解缠隐式形位学习在可伸缩六维位姿估计中的应用
作者：Yilin Wen,Xiangyu Li,Hao Pan,Lei Yang,Zheng Wang,Taku Komura,Wenping Wang
机构：The University of Hong Kong ,Brown University ,Microsoft Research Asia ,SUSTech
链接：https://arxiv.org/abs/2107.12549

医学相关(1篇)

【1】 Technical Report: Quality Assessment Tool for Machine Learning with Clinical CT
标题：技术报告：结合临床CT的机器学习质量评估工具
作者：Riqiang Gao,Mirza S. Khan,Yucheng Tang,Kaiwen Xu,Steve Deppen,Yuankai Huo,Kim L. Sandler,Pierre P. Massion,Bennett A. Landman
机构：Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA , Vanderbilt University Medical Center, Nashville, TN, USA , Department of Biomedical Informatics, Vanderbilt University, Nashville, TN
备注：18 pages, 13 figures, technical report
链接：https://arxiv.org/abs/2107.12842

GAN|对抗|攻击|生成相关(2篇)

【1】 Image Scene Graph Generation (SGG) Benchmark
标题：图像场景图生成(SGG)基准测试
作者：Xiaotian Han,Jianwei Yang,Houdong Hu,Lei Zhang,Jianfeng Gao,Pengchuan Zhang
机构：Microsoft Cloud + AI, Microsoft Research at Redmond
链接：https://arxiv.org/abs/2107.12604

【2】 Adversarial Attacks with Time-Scale Representations
标题：具有时间尺度表示的对抗性攻击
作者：Alberto Santamaria-Pang,Jianwei Qiu,Aritra Chowdhury,James Kubricht,Peter Tu,Iyer Naresh,Nurali Virani
机构：GE Research, Research Circle, Niskayuna, NY
链接：https://arxiv.org/abs/2107.12473

自动驾驶|车辆|车道检测等(2篇)

【1】 Predicting Take-over Time for Autonomous Driving with Real-World Data: Robust Data Augmentation, Models, and Evaluation
标题：用真实数据预测自动驾驶的接管时间：稳健的数据增强、模型和评估
作者：Akshay Rangesh,Nachiket Deo,Ross Greer,Pujitha Gunaratne,Mohan M. Trivedi
机构： Laboratory for Intelligent & Safe Automobiles, UC San Diego, Toyota Collaborative Safety Research Center
备注：Journal version of arXiv:2104.11489
链接：https://arxiv.org/abs/2107.12932

【2】 Analyzing vehicle pedestrian interactions combining data cube structure and predictive collision risk estimation model
标题：结合数据立方体结构和碰撞风险预测模型的车辆行人交互分析
作者：Byeongjoon Noh,Hansaem Park,Hwasoo Yeo
机构：: Applied Science Research Institute, Korea Advanced Institute of Science and Technology, Daehak-, : Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and, Technology, Daehak-ro, Yuseung-gu, Daejeon, Republic of Korea
备注：33 pages, 19 figures
链接：https://arxiv.org/abs/2107.12507

人脸|人群计数(3篇)

【1】 Learning Local Recurrent Models for Human Mesh Recovery
标题：用于人体网格恢复的学习局部递归模型
作者：Runze Li,Srikrishna Karanam,Ren Li,Terrence Chen,Bir Bhanu,Ziyan Wu
机构：United Imaging Intelligence, Cambridge MA, USA, University of California Riverside, Riverside CA, USA
备注：10 pages, 6 figures, 2 tables
链接：https://arxiv.org/abs/2107.12847

【2】 Rethinking Counting and Localization in Crowds:A Purely Point-Based Framework
标题：重新思考人群中的计数和定位：一个纯粹基于点的框架
作者：Qingyu Song,Changan Wang,Zhengkai Jiang,Yabiao Wang,Ying Tai,Chengjie Wang,Jilin Li,Feiyue Huang,Yang Wu
机构：Tencent Youtu Lab,Applied Research Center (ARC), Tencent PCG
备注：To be appear in ICCV2021 (Oral)
链接：https://arxiv.org/abs/2107.12746

【3】 Uniformity in Heterogeneity:Diving Deep into Count Interval Partition for Crowd Counting
标题：异质性中的一致性：深入计数区间划分进行人群计数
作者：Changan Wang,Qingyu Song,Boshen Zhang,Yabiao Wang,Ying Tai,Xuyi Hu,Chengjie Wang,Jilin Li,Jiayi Ma,Yang Wu
机构：Tencent Youtu Lab,Applied Research Center (ARC), Tencent PCG, Department of Electronic & Electrical Engineering, University College London, United Kingdom, Electronic Information School, Wuhan University, Wuhan, China
备注：To be appear in ICCV2021
链接：https://arxiv.org/abs/2107.12619

跟踪(1篇)

【1】 VIPose: Real-time Visual-Inertial 6D Object Pose Tracking
标题：VIPose：实时视觉惯性6D目标姿态跟踪
作者：Rundong Ge,Giuseppe Loianno
机构：The authors are with the New York University, Tandon School ofEngineering
备注：Accepted by The IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2021
链接：https://arxiv.org/abs/2107.12617

裁剪|量化|加速|压缩相关(1篇)

【1】 COPS: Controlled Pruning Before Training Starts
标题：警察：训练开始前有控制的修剪
作者：Paul Wimmer,Jens Mehnert,Alexandru Condurache
机构： Controlled Pruning Before Training StartsWimmer PaulImage ProcessingRobert Bosch GmbH & Lübeck University7 1 2 29 Leonberg, Condurache AlexandruEngineering Cognitive SystemsRobert Bosch GmbH & Lübeck University70 499 Stuttgart
备注：Accepted by The International Joint Conference on Neural Network (IJCNN) 2021
链接：https://arxiv.org/abs/2107.12673

视觉解释|视频理解VQA|caption等(1篇)

【1】 Greedy Gradient Ensemble for Robust Visual Question Answering
标题：贪婪梯度集成在鲁棒视觉问答中的应用
作者：Xinzhe Han,Shuhui Wang,Chi Su,Qingming Huang,Qi Tian
机构：Key Lab of Intell. Info. Process., Inst. of Comput. Tech., CAS, Beijing, China, University of Chinese Academy of Sciences, Beijing, China, Kingsoft Cloud, Beijing, China, Peng Cheng Laboratory, Shenzhen, China, Cloud BU, Huawei Technologies, Shenzhen, China.
备注：Accepted by ICCV 2021. Code: this https URL
链接：https://arxiv.org/abs/2107.12651

超分辨率|去噪|去模糊|去雾(1篇)

【1】 BridgeNet: A Joint Learning Network of Depth Map Super-Resolution and Monocular Depth Estimation
标题：BridgeNet：深度图超分辨率与单目深度估计的联合学习网络
作者：Qi Tang,Runmin Cong,Ronghui Sheng,Lingzhi He,Dan Zhang,Yao Zhao,Sam Kwong
机构：Institute of Information Science, Beijing Jiaotong University, Beijing, China, Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China, UISEE Technology (Beijing) Co., Ltd. Beijing, China
备注：10 pages, 7 figures, Accepted by ACM MM 2021
链接：https://arxiv.org/abs/2107.12541

点云|SLAM|雷达|激光|深度RGBD相关(1篇)

【1】 CKConv: Learning Feature Voxelization for Point Cloud Analysis
标题：CKConv：点云分析的学习特征体素化
作者：Sungmin Woo,Dogyoon Lee,Junhyeop Lee,Sangwon Hwang,Woojin Kim,Sangyoun Lee
机构：Yonsei University
链接：https://arxiv.org/abs/2107.12655

多模态(2篇)

【1】 Angel's Girl for Blind Painters: an Efficient Painting Navigation System Validated by Multimodal Evaluation Approach
标题：盲人画家的天使女孩：一种多模态评价验证的高效绘画导航系统
作者：Hang Liu,Menghan Hu,Yuzhen Chen,Qingli Li,Guangtao Zhai,Simon X. Yang,Xiao-Ping Zhang,Xiaokang Yang
备注：13 pages, 18 figures
链接：https://arxiv.org/abs/2107.12921

【2】 Multi-modal estimation of the properties of containers and their content: survey and evaluation
标题：集装箱及其内容物性能的多模态估计：调查与评价
作者：Alessio Xompero,Santiago Donaher,Vladimir Iashin,Francesca Palermo,Gökhan Solak,Claudio Coppola,Reina Ishikawa,Yuichi Nagao,Ryo Hachiuma,Qi Liu,Fan Feng,Chuanlin Lan,Rosa H. M. Chan,Guilherme Christmann,Jyun-Ting Song,Gonuguntla Neeharika,Chinnakotla Krishna Teja Reddy,Dinesh Jain,Bakhtawar Ur Rehman,Andrea Cavallaro
机构： are with Keio University
备注：13 pages, 9 tables, 5 figures, submitted to IEEE Transactions on Multimedia
链接：https://arxiv.org/abs/2107.12719

3D|3D重建等相关(1篇)

【1】 Language Grounding with 3D Objects
标题：3D对象的语言基础
作者：Jesse Thomason,Mohit Shridhar,Yonatan Bisk,Chris Paxton,Luke Zettlemoyer
机构：University of Southern California, University of Washington, Carnegie Mellon University, NVIDIA
备注：this https URL
链接：https://arxiv.org/abs/2107.12514

其他神经网络|深度学习|模型|建模(8篇)

【1】 StarEnhancer: Learning Real-Time and Style-Aware Image Enhancement
标题：StarEnhizer：学习实时和样式感知的图像增强
作者：Yuda Song,Hui Qian,Xin Du
机构：College of Computer Science and Technology, Zhejiang University, Hangzhou, China, College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China
链接：https://arxiv.org/abs/2107.12898

【2】 RGL-NET: A Recurrent Graph Learning framework for Progressive Part Assembly
标题：RGL-Net：递归的零件装配图学习框架
作者：Abhinav Narayan Harish,Rajendra Nagar,Shanmuganathan Raman
机构：Indian Institute of Technology Gandhinagar, Indian Institute of Technology Jodhpur
备注：Accepted to Winter Conference of Computer Vision (WACV 2022)
链接：https://arxiv.org/abs/2107.12859

【3】 Deep Reinforcement Learning for L3 Slice Localization in Sarcopenia Assessment
标题：深度强化学习在肉质减少症L3切片定位中的应用
作者：Othmane Laousy,Guillaume Chassagnon,Edouard Oyallon,Nikos Paragios,Marie-Pierre Revel,Maria Vakalopoulou
链接：https://arxiv.org/abs/2107.12800

【4】 Continual Learning with Neuron Activation Importance
标题：持续学习与神经元激活的重要性
作者：Sohee Kim,Seungkyu Lee
机构：Kyunghee University, Department of Computer Engineering, Yongin, Republic of Korea
链接：https://arxiv.org/abs/2107.12657

【5】 Co-Transport for Class-Incremental Learning
标题：用于班级增量学习的协同传输
作者：Da-Wei Zhou,Han-Jia Ye,De-Chuan Zhan
机构：State Key Laboratory for Novel Software Technology, Nanjing University
备注：Accepted to ACM Multimedia 2021
链接：https://arxiv.org/abs/2107.12654

【6】 Identify Apple Leaf Diseases Using Deep Learning Algorithm
标题：基于深度学习算法的苹果叶部病害识别
作者：Daping Zhang,Hongyu Yang,Jiayu Cao
链接：https://arxiv.org/abs/2107.12598

【7】 Towards Efficient Tensor Decomposition-Based DNN Model Compression with Optimization Framework
标题：优化框架下基于张量分解的DNN模型压缩
作者：Miao Yin,Yang Sui,Siyu Liao,Bo Yuan
机构：Department of ECE, Rutgers University,Amazon
备注：This paper was accepted to CVPR'21
链接：https://arxiv.org/abs/2107.12422

【8】 SaRNet: A Dataset for Deep Learning Assisted Search and Rescue with Satellite Imagery
标题：SARNET：一种卫星影像深度学习辅助搜救数据集
作者：Michael Thoreau,Frazer Wilson
机构：Department of Electrical and Computer Engineering, New York University, No Affiliation
链接：https://arxiv.org/abs/2107.12469

其他(5篇)

【1】 Improving ClusterGAN Using Self-AugmentedInformation Maximization of Disentangling LatentSpaces
标题：基于解缠延迟空间自增强信息最大化的聚类GAN改进
作者：Tanmoy Dam,Sreenatha G. Anavatti,Hussein A. Abbass
机构：School of Engineering and Information Technology, University of New South Wales Canberra, Australia.
备注：This paper is under review to IEEE TNNLS
链接：https://arxiv.org/abs/2107.12706

【2】 Vision-Guided Forecasting -- Visual Context for Multi-Horizon Time Series Forecasting
标题：视觉引导预测--多层次时间序列预测的视觉语境
作者：Eitan Kosman,Dotan Di Castro
机构：Technion - Israel Institute of Technology, Bosch Center for Artificial Intelligence
链接：https://arxiv.org/abs/2107.12674

【3】 Computer Vision-Based Guidance Assistance Concept for Plowing Using RGB-D Camera
标题：基于计算机视觉的RGB-D相机辅助犁耕方案
作者：Erkin Türköz,Ertug Olcay,Timo Oksanen
机构：Technical University of Munich, School of Life Sciences, Chair of Agrimechatronics, Freising, Germany, © , IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including
备注：Accepted to be published in Proceedings of the 2021 IEEE International Conference on Imaging Systems and Techniques, August 24-26 2021
链接：https://arxiv.org/abs/2107.12646

【4】 CalCROP21: A Georeferenced multi-spectral dataset of Satellite Imagery and Crop Labels
标题：CalCROP21：卫星图像和作物标签的地理参考多光谱数据集
作者：Rahul Ghosh,Praveen Ravirathinam,Xiaowei Jia,Ankush Khandelwal,David Mulla,Vipin Kumar
机构：University of Minnesota, Minneapolis, MN, USA, University of Pittsburgh, Pittsburgh, PA, USA, St. Paul, MN, USA
备注：13 pages; 11 figures
链接：https://arxiv.org/abs/2107.12499

【5】 Circular-Symmetric Correlation Layer based on FFT
标题：基于FFT的圆对称相关层
作者：Bahar Azari,Deniz Erdogmus
机构：Department of Electrical & Computer Engineering, Northeastern University, USA, Boston, MA , Deniz Erdo˘gmu¸s
链接：https://arxiv.org/abs/2107.12480

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