Group 1 - The People's Bank of China conducted a reverse repurchase operation of 342.5 billion yuan for a 7-day term [3] - The U.S. stock market showed mixed results with the Dow Jones down 0.04%, Nasdaq up 0.38%, and S&P 500 up 0.14% [4] - International precious metals futures saw a general increase, with COMEX gold futures rising by 1.55% to $3410.3 per ounce and COMEX silver futures up 2.02% to $39.24 per ounce [5] Group 2 - International oil prices slightly declined, with WTI crude oil down 0.41% to $65.78 per barrel and Brent crude down 0.36% to $69.03 per barrel [6] - European stock indices closed mixed, with Germany's DAX up 0.08% to 24307.8 points, France's CAC40 down 0.31% to 7798.22 points, and the UK's FTSE 100 up 0.23% to 9012.99 points [7] Group 3 - The State Council of China announced the implementation of the "Housing Rental Regulations" effective from September 15, 2025, aimed at regulating rental activities and promoting high-quality development in the housing rental market [8] - The Ministry of Commerce of China expressed strong opposition to the EU's sanctions against Chinese companies and financial institutions in the 18th round of sanctions against Russia [8] Group 4 - BYD celebrated the rollout of its 13 millionth new energy vehicle, with domestic sales exceeding 2.113 million units in the first half of 2025, a year-on-year increase of 31.5% [15] - JD.com made significant investments in three leading companies in the field of embodied intelligence, indicating a strong focus on technological innovation [16] Group 5 - Dingdong Maicai announced its "4G" strategy to differentiate itself in the market, focusing on quality products and services to escape homogenization [20] - China Petroleum & Chemical Corporation (Sinopec) invested in Fengdeng Green Energy Environmental Protection Co., becoming its second-largest shareholder, which will support the construction of "waste-free parks" [23] Group 6 - GoerTek submitted an application for listing on the Hong Kong Stock Exchange, which is expected to attract more investor attention [24] - Wenyan Zhixing and Lenovo collaborated to launch a high-performance computing platform, which is anticipated to enhance competitiveness in the autonomous driving sector [26]

Core Viewpoint - The article discusses the evolving landscape of 4D annotation in autonomous driving, emphasizing the shift from traditional SLAM techniques to more advanced methods for static element reconstruction and automatic labeling [1][4]. Group 1: Purpose and Applications of Reconstruction - The primary purposes of reconstruction are to create 3D maps from lidar or multiple cameras and to output vector lane lines and categories [5][6]. - The application of 4D annotation in static elements remains broad, with a focus on lane markings and static obstacles, which require 2D spatial annotations at each timestamp [1][6]. Group 2: Challenges in Automatic Annotation - The challenges in 4D automatic annotation include high temporal consistency requirements, complex multi-modal data fusion, difficulties in generalizing dynamic scenes, conflicts between annotation efficiency and cost, and high demands for scene generalization in production [8][9]. - These challenges hinder the iterative efficiency of data loops in autonomous driving, impacting the system's generalization capabilities and safety [8]. Group 3: Course Structure and Content - The course on 4D automatic annotation covers a comprehensive curriculum, including dynamic obstacle detection, SLAM reconstruction principles, static element annotation based on reconstruction graphs, and the end-to-end truth generation process [9][10][17]. - Each chapter includes practical exercises to enhance understanding and application of the algorithms discussed [9][10]. Group 4: Instructor and Target Audience - The course is led by an industry expert with extensive experience in multi-modal 3D perception and data loop algorithms, having participated in multiple production delivery projects [21]. - The target audience includes researchers, students, and professionals looking to transition into the data loop field, requiring a foundational understanding of deep learning and autonomous driving perception algorithms [24][25].