此外，摩根士丹利将2025年内地汽车销售上调6%至2990万辆，意味按年升9%，因预期刺激政策到期前 将出现提前购车潮，以及近期多款新车型上市有望推动第四季批发销售。大摩将禾赛目标价上调至35美 元，予"增持"评级。(格隆汇) 禾赛(HSAI.US)盘前涨超7%，报23.62美元。消息面上，禾赛宣布，2025年度第100万台激光雷达已于9 月底正式生产下线。禾赛成为全球首个年产量突破百万台的激光雷达企业，将以"年百万级"超大规模量 产交付能力继续引领激光雷达行业标准。这一里程碑也标志着禾赛科技阶段性实现了其创业以来的首个 企业愿景，即"2025年让全球1%的车辆具备三维感知能力。" ...

在三维重建不断走向工程化的今天，前馈式3D Gaussian Splatting（Feed-Forward 3DGS）正火速走向产业化。 然而，现有的前馈3DGS方法主要采用"像素对齐"（pixel-aligned）策略——即将每个2D像素单独映射到一个或多个3D高斯上。 这一做法看似直观，但仍面临两道不可忽视的"天花板"：二维特征难以在三维中精确对齐、以及高斯基元数量被像素网格死死绑定，无法按 场景复杂度智能分配。 VolSplat团队 投稿 量子位 | 公众号 QbitAI VolSplat 大胆抛弃像素对齐的固有范式，提出"体素对齐"（voxel-aligned）的前馈框架：在三维空间中融合视图信息，从根本上破局，让 高质量的多视角渲染变得更鲁棒、更高效、更易工程化。 VolSplat 的核心思路：把"对齐"从二维搬到三维 原有的像素对齐前馈3DGS ，正面临两项无法回避的痛点。 第一， 多视图对齐难题 ：基于2D特征的匹配难以可靠地解决多视角间的几何一致性问题——当深度估计不稳、遮挡或视角差异出现时， 2D特征难以在三维空间里精确对齐，常导致浮空伪影与几何畸变。 在公开数据集上的对比实验显示，VolS ...

华中科技大学14日发布消息，该校联合清华大学、北京信息科技大学，研发一种全新的"双模态"激光雷 达系统，为自动驾驶汽车、机器人、无人机等设备的三维感知能力带来进一步提升。 相关成果于近日 发表于国际光学期刊《光：科学与应用》(Light：Science & Applications)。 ...

Core Viewpoint - Chinese scientists have successfully developed a new "dual-mode" LiDAR system that enhances the three-dimensional perception capabilities of autonomous vehicles, robots, and drones [1][4]. Group 1: Technology Development - The "dual-mode" LiDAR system was developed by a team from Huazhong University of Science and Technology in collaboration with Tsinghua University and Beijing Information Science and Technology University, and published in the top international optical journal "Light: Science & Applications" [1]. - Traditional LiDAR systems are categorized into scanning and flash types, with the former offering high precision but slow speed, while the latter provides fast speed but limited precision. The new system aims to combine the advantages of both [1][4]. Group 2: System Functionality - The core of the new system is a device called "hybrid cascaded translational metasurface," which consists of two layers of specially designed nano-lenses. By altering the polarization state of the incident laser, the system can switch between high-precision scanning mode and flash mode [1][2]. - The hardware allows the system to automatically switch modes based on actual needs, first using flash mode to quickly gather environmental information, then switching to scanning mode for detailed detection of specific areas [2]. Group 3: Implications and Future Applications - This technology successfully integrates the advantages of traditional scanning and flash LiDAR, ensuring high precision and long-distance detection while improving detection efficiency [4]. - The more efficient, flexible, and compact "dual-mode" LiDAR is expected to play a significant role in the fields of autonomous vehicles, intelligent robots, and drones, enhancing their ability to perceive the world [4].