Remote photoplethysmography (rPPG), a family of techniques for monitoring blood volume changes, may be especially useful for widespread contactless health monitoring using face video from consumer-grade visible-light cameras. The COVID-19 pandemic has caused the widespread use of protective face masks. We found that occlusions from cloth face masks increased the mean absolute error of heart rate estimation by more than 80\% when deploying methods designed on unmasked faces. We show that augmenting unmasked face videos by adding patterned synthetic face masks forces the model to attend to the periocular and forehead regions, improving performance and closing the gap between masked and unmasked pulse estimation. To our knowledge, this paper is the first to analyse the impact of face masks on the accuracy of pulse estimation and offers several novel contributions: (a) 3D CNN-based method designed for remote photoplethysmography in a presence of face masks, (b) two publicly available pulse estimation datasets acquired from 86 unmasked and 61 masked subjects, (c) evaluations of handcrafted algorithms and a 3D CNN trained on videos of unmasked faces and with masks synthetically added, and (d) data augmentation method to add a synthetic mask to a face video.
MaskCD: A Remote Sensing Change Detection Network Based on Mask Classification
Helmholtz Institute Freiberg for Resource Technology（弗莱贝格亥姆霍兹资源技术研究所）；Helmholtz-Zentrum Dresden-Rossendorf（德累斯顿-罗森多夫亥姆霍兹中心）；Technical University of Munich (TUM)（慕尼黑工业大学）；School of Information Science and Engineering, Wuhan University of Science and Technology（武汉科技大学信息科学与工程学院）；School of Engineering, Shiv Nadar University（希夫·纳达尔大学工程学院）；Munich Center for Machine Learning（慕尼黑机器学习中心）；Lancaster University（兰卡斯特大学）
Next-Frequency Autoregressive Modeling for Remote Sensing Change Detection
Zhejiang Lab（之江实验室）；Beijing University of Posts and Telecommunications（北京邮电大学）；Changsha University of Science and Technology（长沙理工大学）；The Education University of Hong Kong（香港教育大学）；South China Agricultural University（华南农业大学）
Small Target Detection Based on Mask-Enhanced Attention Fusion of Visible and Infrared Remote Sensing Images
National Space Science Center, Chinese Academy of Sciences（中国科学院国家空间科学中心）；School of Computer Science and Technology, University of Chinese Academy of Sciences（中国科学院大学计算机科学与技术学院）；School of Electronic Engineering and Computer Science, Queen Mary University of London（伦敦大学玛丽女王学院电子工程与计算机科学学院）；School of Astronomy and Space Science, University of Chinese Academy of Sciences（中国科学院大学天文学与空间科学学院）
Masks Can Talk: Extracting Structured Text Information from Single-Modal Images for Remote Sensing Change Detection
Zhejiang University（浙江大学）；Harbin Institute of Technology（哈尔滨工业大学）；Harbin Institute of Technology Suzhou Research Institute（哈尔滨工业大学苏州研究院）；North China University of Water Resources and Electric Power（华北水利水电大学）；University of Auckland（奥克兰大学）
Mask Approximation Net: A Novel Diffusion Model Approach for Remote Sensing Change Captioning
School of Computer Science and Technology and the Ministry of Education Key Lab for Intelligent Networks and Network Security, Xi’an Jiaotong University（计算机科学与技术学院和教育部智能网络与网络安全重点实验室，西安交通大学）；Aerospace Information Research Institute, Chinese Academy of Sciences（航天信息研究所，中国科学院）；Space Engineering University（航天工程大学）；School of Mathematics and Statistics, Guangdong University of Technology（数学与统计学院，广东工业大学）；Helmholtz-Zentrum Dresden-Rossendorf（德累斯顿-罗斯托克亥姆霍兹中心）
GeoGround: A Unified Large Vision-Language Model for Remote Sensing Visual Grounding
Nanyang Technological University（南洋理工大学）；University of Reading（阅读大学）；Shanghai Jiao Tong University（上海交通大学）；Harbin Institute of Technology（哈尔滨工业大学）；SenseTime Research（商汤科技研究院）
DiCoR: Decoupled Referent Disambiguation and Contour Recalibration for Efficient Referring Remote Sensing Image Segmentation
School of Information Science and Electronic Engineering, Shanghai Jiao Tong University（上海交通大学信息科学与工程学院）；College of Computer Science, Nankai University（南开大学计算机学院）；Tsinghua Shenzhen International Graduate School, Tsinghua University（清华大学深圳国际研究生院）；Department of Electronic Engineering, Tsinghua University（清华大学电子工程系）
Remote SAMsing: From Segment Anything to Segment Everything
Department of Electrical Engineering, University of Bras\' i lia, Bras\' i lia, Brazil；Department of Geography, University of Bras\' i lia, Bras\' i lia, Brazil
InstructSAM: A Training-Free Framework for Instruction-Oriented Remote Sensing Object Recognition
Aerospace Information Research Institute, Chinese Academy of Sciences（航天信息研究所，中国科学院）；University of Chinese Academy of Sciences（中国科学院大学）；Harbin Institute of Technology（哈尔滨工业大学）；Shanghai Jiao Tong University（上海交通大学）；University of Wollongong（沃林戈大学）；SAIS, Shanghai Jiao Tong University（上海交通大学国际关系学院）
PointSAM: Pointly-Supervised Segment Anything Model for Remote Sensing Images
School of Information Science and Technology, Southwest Jiaotong University（西南交通大学信息科学与技术学院）；I2R, A*STAR（新加坡科研局信息研究院）；South China University of Technology（华南理工大学）
Cross-modal Context-aware Learning for Visual Prompt Guided Multimodal Image Understanding in Remote Sensing
College of Computer Science and Electronic Engineering, Hunan University（计算机科学与电子工程学院，湖南大学）；School of Robotics and the National Engineering Research Center of Robot Visual Perception and Control Technology, Hunan University（机器人学院及机器人视觉感知与控制技术国家工程研究中心，湖南大学）；School of Computing and Artificial Intelligence, Southwest Jiaotong University（计算与人工智能学院，西南交通大学）
VIPL-HR: A Multi-modal Database for Pulse Estimation from Less-constrained Face Video
University of Chinese Academy of Sciences（中国科学院大学）；Peng Cheng Laboratory（鹏城实验室）；CAS Center for Excellence in Brain Science and Intelligence Technology（中国科学院脑科学与智能技术卓越创新中心）
Contrastive Context-Aware Learning for 3D High-Fidelity Mask Face Presentation Attack Detection
MUST（澳门科技大学）；Mininglamp Academy of Sciences, Mininglamp Technology（明略科技集团明略科学院）；NLPR, CASIA, UCAS（中国科学院自动化研究所模式识别国家重点实验室，中国科学院大学）；CVC, UB（巴塞罗那大学计算机视觉中心）；Baidu Research（百度研究院）；Westlake University（西湖大学）；University of Oulu（奥卢大学）
