Mobile service robots can benefit from object-level understanding of their environments, including the ability to distinguish object instances and re-identify previously seen instances. Object re-identification is challenging across different viewpoints and in scenes with significant appearance variation arising from weather or lighting changes. Existing works on object re-identification either focus on specific classes or require foreground segmentation. Further, these methods, along with object re-identification datasets, have limited consideration of challenges such as outdoor scenes and illumination changes. To address this problem, we introduce CODa Re-ID: an in-the-wild object re-identification dataset containing 1,037,814 observations of 557 objects across 8 classes under diverse lighting conditions and viewpoints. Further, we propose CLOVER, a representation learning method for object observations that can distinguish between static object instances without requiring foreground segmentation. We also introduce MapCLOVER, a method for scalably summarizing CLOVER descriptors for use in object maps and matching new observations to summarized descriptors. Our results show that CLOVER achieves superior performance in static object re-identification under varying lighting conditions and viewpoint changes and can generalize to unseen instances and classes.
Viewpoint-Aware Loss with Angular Regularization for Person Re-Identification
Tencent YouTu Lab（腾讯优图实验室）；Sun Yat-sen University（中山大学）；Southern University of Science and Technology（南方科技大学）
虽然最近在监督人重新识别（Re-ID）方面取得了很大进展，但由于人的视角变化，Re-ID仍然是一个巨大的视觉挑战。大多数现有的基于视点的人Re-ID方法将来自每个视点的图像投影到分离且不相关的子特征空间中。它们只对个体视点内部的身份级别分布进行建模，而忽略了不同视点之间的潜在关系。为了解决这个问题，我们提出了一种新的方法，称为\textit{Viewpoint-Aware Loss with Angular Regularization }（\textbf{VA-reID}）。而不是一个子空间为每个视点，我们的方法项目的功能从不同的观点到一个统一的超球，并有效地建模的特征分布的身份级别和视点级别。此外，而不是建模不同的观点作为硬标签用于传统的视点分类，我们引入了视点感知的自适应标签平滑正则化（VALSR），分配自适应软标签的功能表示。VALSR算法能有效地解决视点簇标签分配的模糊性问题。在Market 1501和DukeMTMC-reID数据集上进行的大量实验表明，我们的方法优于最先进的监督Re-ID方法。
View-Aware Semantic Alignment for Aerial-Ground Person Re-Identification
Sun Yat-sen University, China（中山大学，中国）；Pazhou Lab (HuangPu), Guangdong, China（琶洲实验室（黄埔），广东，中国）；Guangdong Province Key Laboratory of Information Security Technology, Guangzhou, China（广东省信息安全技术重点实验室，广州，中国）；Key Laboratory of Machine Intelligence and Advanced Computing, Ministry of Education, China（教育部机器智能与高级计算重点实验室，中国）
CityGuard: Graph-Aware Private Descriptors for Bias-Resilient Identity Search Across Urban Cameras
University of Macau（澳门大学）；Tsinghua University（清华大学）；Renmin University of China（中国人民大学）；Shanghai AI Laboratory（上海人工智能实验室）；The Hong Kong University of Science and Technology（香港科技大学）；Juntendo University（顺天堂大学）；Peking University（北京大学）
Energy-Efficient Uncertainty-Aware Biomass Composition Prediction at the Edge
Saint Louis University（圣路易斯大学）；Technological University Dublin（都柏林理工大学）；Walton Institute（沃尔顿研究所）；South East Technological University（东南理工大学）；Australian Institute of Machine Learning（澳大利亚机器学习研究院）
FedBPrompt: Federated Domain Generalization Person Re-Identification via Body Distribution Aware Visual Prompts
School of Computer Science and Technology, Wuhan University of Science and Technology, China（武汉理工大学计算机科学与技术学院，中国）；NERC for Multimedia Software, School of Computer Science, Wuhan University, China（武汉大学计算机学院，中国）；Nanyang Technological University, Singapore（新加坡南洋理工大学）；Changsha Bus Group, China（中国长沙公交集团）；Central South University of Forestry and Technology, China（中国林业科技大学）；Harbin Institute of Technology Zhengzhou Research Institute, China（哈尔滨工业大学郑州研究院，中国）
The Worse The Better: Content-Aware Viewpoint Generation Network for Projection-related Point Cloud Quality Assessment
School of Automation, Nanjing University of Science and Technology（南京理工大学自动化学院）；School of Computer Science and Engineering, Nanjing University of Science and Technology（南京理工大学计算机科学与工程学院）
4DGC: Rate-Aware 4D Gaussian Compression for Efficient Streamable Free-Viewpoint Video
Cooperative Medianet Innovation Center, Shanghai Jiao Tong University（上海交通大学合作Medianet创新中心）；School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University（上海交通大学电子信息与电气工程学院）；School of Artificial Intelligence, Shanghai Jiao Tong University（上海交通大学人工智能学院）
CricaVPR: Cross-image Correlation-aware Representation Learning for Visual Place Recognition
Tsinghua Shenzhen International Graduate School, Tsinghua University（清华大学深圳国际研究生院）；Peng Cheng Laboratory（鹏城实验室）；University of Chinese Academy of Sciences（中国科学院大学）
Neural Free-Viewpoint Performance Rendering under Complex Human-object Interactions
ShanghaiTech University（上海科技大学）；Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences（中国科学院上海微系统与信息技术研究所）；University of Chinese Academy of Sciences（中国科学院大学）
SafeVantage: Vantage-Aware Memory for Reliable Embodied Decisions
Massachusetts Institute of Technology（麻省理工学院）；Korea Advanced Institute of Science and Technology（韩国科学技术院）；Nanyang Technological University（南洋理工大学）；Tsinghua University（清华大学）
Embody4D: A Generalist Data Engine for Embodied 4D World Modeling
Zhejiang University（浙江大学）；Beijing Zhongguancun Academy（北京中关村学院）；University of Science and Technology of China（中国科学技术大学）；Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；Shanghai Jiao Tong University（上海交通大学）；Beihang University（北京航空航天大学）
