深蓝AI . 专注于人工智能、机器人与自动驾驶的学习平台。 来源 | 深蓝AI 原文链接： 纯视觉方案！中山大学&港科大新作：基于3DGS实现高精度轨迹视频生成 点击下方 卡片 ，关注" 自动驾驶之心 "公众号 戳我-> 领取 自动驾驶近30个 方向 学习 路线 >>自动驾驶前沿信息获取 → 自动驾驶之心知识星球 本文只做学术分享，如有侵权，联系删文 「 不修图、不依赖 LiDAR 」 以下文章来源于深蓝AI ，作者深蓝学院 在自动驾驶领域， 多轨迹、多视角的视频数据 几乎是刚需。 它不仅决定了 3D 重建的完整性，也直接影响世界模型和规划系统的泛化能力。但现实很骨感： 真实世界里，想采集同一条道路、不同横向位置、严格同步的多条驾驶视频，成本极高。要么多车协同，要么反复跑同一路段，还会带来时间、动态目 标不一致的问题。于是，研究者开始尝试： 能不能只用一条真实驾驶视频，自动"生成"另一条相邻轨迹的视频？ 看似简单，实际却踩了两个大坑： 中山大学与香港科技大学提出了ReCamDriving，一个完全基于视觉、却能精确控制相机轨迹的新轨迹视频生成方法。 不修补、不靠 LiDAR，直接换一种相机控制思路。 标题： ...

点击下方 卡片 ，关注" 自动驾驶之心 "公众号 戳我-> 领取 自动驾驶近30个 方向 学习 路线 名额有限，仅限前「5名」 最近一个月，柱哥在星球内更新了很多最新的行业动态： 同时，还有很多的答疑解惑： Waymo最新的基座模型分享，快慢双系统+数据飞轮； 2025地平线技术生态大会上，苏箐关于自驾的一些insights； 自动驾驶世界模型论文与代码汇总； 英伟达2025年技术图鉴，自驾、具身、大模型全面开花； 理想披露了的最新技术信息，从数据闭环到训练闭环。 近期柱哥也会邀请嘉宾在星球内部和大家聊一聊最近的一些技术进展，欢迎大家加入自动驾驶之心知识星球。 我们准备了大额新人优惠...... 秋招/社招offer建议； 传统规控实现给端到端大模型兜底的思路； 动态行人的场景高斯重建的方法； 40个问题深度解析自动驾驶领域vla+wm的重磅工作：DriveVLA-W0； BEV融合如何能够提升盲区（很近范围）内3D Box的边界准确程度； 小鹏第二代VLA的延展讨论； 对于很多想入门的同学来说，试错成本有点高。没时间和缺乏完整的体系是最大问题，这也容易导致行业壁垒 越来越高，如果想要卷赢那就更加困难了。 扛 ...

点击下方 卡片 ，关注" 自动驾驶之心 "公众号 戳我-> 领取 自动驾驶近30个 方向 学习 路线 >>自动驾驶前沿信息获取 → 自动驾驶之心知识星球 今年整个自动驾驶行业融资已经超过300亿！其中L4相关公司的融资比较密集，柱哥周末盘了下部分公司的融资情况，分享给大家。据我 们了解，这其中很多公司也在抓紧落地端到端、VLA等核心技术， 明年将会是L4大爆发的一年。 新石器 新石器今年完成了C+轮和D轮两起融资，2025年2下旬的10亿C+轮融资，和10月23日的D轮超6亿美元融资。D轮融资由阿联酋磊石资本领 投，高成投资、信宸资本、鼎晖VGC等机构联合领投。 以金额计，该融资是迄今为止中国自动驾驶领域最大的一笔私募融资。 公司简介： 成立时间：2018 年 2 月，创始人余恩源 定位：全球领先的 L4 级无人城配 (RoboVan) 解决方案提供商，专注城市物流 "最后一公里" 技术：全栈自研 L4 级无图自动驾驶技术，已交付超 1 万台无人车，累计行驶里程超 5000 万公里 核心产品：RoboVan 系列无人配送车，覆盖快递、即时物流、零售等多场景 里程碑：2025 年累计融资超 62 亿元，产品已拓 ...

以下文章来源于自动驾驶数据挖掘 ，作者黑客与作家 自动驾驶数据挖掘 作者 | 黑客与作家 来源 | 自动驾驶数据挖掘 原文链接： 【E2E训练】首创！同济孙剑团队三层框架解析端到端自动驾驶训练生态！ 点击下方 卡片 ，关注" 自动驾驶之心 "公众号 戳我-> 领取 自动驾驶近30个 方向 学习 路线 >>自动驾驶前沿信息获取 → 自动驾驶之心知识星球 本文只做学术分享，如有侵权，联系删文 导读 破解"训练碎片化"痛点！现有端到端自动驾驶（E2E-AD）训练存在数据堆砌、策略孤立、平台割裂三大问题，导致模型泛化弱、部署难。同济大学 +UNC联合发布 Data-Strategy-Platform三层训练生态框架 ，实现三重核心突破： ① 数据层从 "规模扩张"转向"价值密度" ，聚焦 高风险/长尾场景 ； ② 策略层从 "任务级拼接"升级为"能力型基础" ，涵盖IL/RL到生成式范式（扩散/LLM/世界模型）； ③ 平台层从 "静态离线"进化为"持续闭环" ，整合分布式训练、云边协同与灰度发布。 该综述整合280+论文、6大车企工业实践，明确未来三大趋势，为E2E-AD从科研走向量产提供系统级"训练导航图"。 图 ...

以下文章来源于3D视觉之心 ，作者Zhankuo Xu等 3D视觉之心 . 3D视觉与具身智能、机器人相关内容分享。 点击下方 卡片 ，关注" 3D视觉之心 "公众号 第一时间获取 3D视觉干货 3D高斯 splatting（3DGS）能生成超逼真的3D场景，但它有个短板—— 依赖密集、清晰的输入图像 。而现实中 手持拍摄的照片往往又少又模糊，这会形成一个"恶性循环"：稀疏视图缺乏多视角约束，没法消除运动模糊；而 运动模糊又会抹掉细节，让仅有的几个视图难以对齐，最终重建出的3D场景要么支离破碎，要么满是噪点。 北京大学团队推出的CoherentGS，很好的打破了这个循环！它靠"双先验引导"策略，只用3~9张稀疏模糊的照 片，就能重建出高清、连贯的3D场景。不管是手持拍摄的模糊素材，还是视角稀少的场景，都能轻松应对。 CoherentGS的突破，是同时解决"去模糊"和"补全几何"两个核心问题，用双先验协同引导优化，让稀疏模糊的输 入也能产出高质量3D重建。 核心框架：双先验联手，破解双重难题 图3. CoherentGS系统 图3是CoherentGS的整体流程，左侧是用COLMAP初始化高斯和相机位姿；上方通 ...

Core Insights - The article emphasizes the growing importance of embodied intelligence as a key technology trend globally, with numerous companies emerging in this field, both domestically and internationally [1][5][9]. Group 1: Industry Trends - There is a significant talent gap in the embodied intelligence sector, with many master's graduates being pre-booked for positions [1]. - High-profile executives from various industries, including autonomous driving, are transitioning to startups in the embodied intelligence space [1]. - A community platform, "Embodied Intelligence Heart Knowledge Circle," has been established to facilitate knowledge sharing and networking among industry professionals [1][9]. Group 2: Community and Learning Resources - The community offers continuous live sharing sessions, including roundtable discussions and webinars, to keep members informed about developments and challenges in the embodied intelligence industry [3]. - A comprehensive technical roadmap has been created for beginners, outlining essential technologies and learning paths in the field [5]. - Valuable industry frameworks and project proposals are provided for those already engaged in related research [7]. Group 3: Job Opportunities and Networking - The community has established a job referral mechanism with various embodied intelligence companies, facilitating connections between job seekers and employers [9]. - Members have access to exclusive learning materials and can interact with industry leaders for guidance on career and research choices [13][9]. Group 4: Research and Development - The community compiles a wide range of open-source projects, datasets, and simulation platforms relevant to embodied intelligence, aiding both newcomers and experienced professionals [10][25]. - A collection of research reports and academic resources related to embodied intelligence and robotics is available for members to stay updated on industry advancements [18][17].

Core Viewpoint - The article discusses the distinction between world models and end-to-end models in autonomous driving, emphasizing that world models are a means to achieve end-to-end autonomous driving rather than a specific technology [2]. Group 1: World Model Overview - The article highlights the recent surge in publications related to world models, particularly in the context of closed-loop simulation, which is becoming a trend in the industry due to the high costs associated with corner cases [2]. - It introduces a new course focused on world models, covering various algorithms such as general world models, video generation, and OCC generation, with applications in Tesla's world model and the Marble project by Fei-Fei Li's team [2][5]. Group 2: Course Structure - The course consists of six chapters, starting with an introduction to world models and their relationship with end-to-end autonomous driving, followed by a discussion on the historical development and current applications of world models [5][6]. - The second chapter covers foundational knowledge related to world models, including scene representation and technologies like Transformer and BEV perception, which are crucial for understanding subsequent chapters [5][6]. Group 3: Advanced Topics - The third chapter focuses on general world models, discussing notable models such as Marble, Genie 3 from DeepMind, and the latest developments from Meta, including the VLA+ world model algorithm [6][7]. - The fourth chapter delves into video generation-based world models, presenting classic works and recent advancements in the field, including projects like GAIA-1 & GAIA-2 and OpenDWM [7][8]. - The fifth chapter addresses OCC generation methods, explaining their potential for trajectory planning and end-to-end implementation [8]. Group 4: Industry Application and Career Preparation - The sixth chapter provides insights into the practical applications of world models in the industry, discussing pain points and how to prepare for job interviews in this field [9]. - The course aims to equip participants with the skills to understand and implement world model technologies, preparing them for roles as world model algorithm engineers [10][13].

Core Viewpoint - The article discusses the rapid growth and market dynamics of urban NOA (Navigation on Autopilot) suppliers, highlighting the strategic investments and partnerships that are shaping the industry landscape [4][5]. Group 1: Investment and Market Position - Yuanrong has secured strategic investments from leading Tier 1 suppliers and luxury car manufacturers, indicating strong industry interest in high-quality urban NOA suppliers [4]. - Major players like Huawei, Yuanrong, and Momenta each hold over one million urban NOA project orders, suggesting a competitive market structure [5]. Group 2: Growth and Market Trends - Yuanrong has delivered 200,000 vehicles equipped with urban NOA, achieving a nearly 40% market share in the third-party supplier market by October 2025 [4]. - The urban NOA market is expected to experience significant growth, surpassing highway NOA as the mainstream solution due to the increasing adoption and technological advancements [4][6]. Group 3: Future Projections and Challenges - By 2026, urban NOA is projected to see a major surge in volume, driven by reduced hardware costs and the integration of intelligent driving in traditional fuel vehicles, potentially adding millions of units to the market [6]. - Achieving a production scale of over one million units will be a critical milestone for leading intelligent driving companies, as it will help establish data barriers and competitive advantages [6][7]. Group 4: Technological Evolution - The article emphasizes the importance of technological iteration, particularly the transition from VLA (Vehicle Level Automation) from initial production to significant performance improvements in 2026 [7]. - Companies must balance the need for cost-effective urban NOA solutions with advancements in cutting-edge technologies to remain competitive in the evolving market [8].

来源 | 雷峰网 点击下方 卡片 ，关注" 自动驾驶之心 "公众号 戳我-> 领取 自动驾驶近30个 方向 学习 路线 >>自动驾驶前沿信息获取 → 自动驾驶之心知识星球 以下文章来源于雷峰网 ，作者智驾情报局 雷峰网 . 洞见智能未来，共与产业变迁 本文只做学术分享，如有侵权，联系删文 智驾公司高层内斗或为停摆元凶，欺上瞒下失信集团被全面接管 上期雷峰网聊到智驾独角兽 A 停摆，是因为其在技术方面存在硬伤，但实际上A公司早就因人事管理问题被集团B全面接管。 据知情人爆料，早在上个月公司通过群聊通知停工消息前，该公司的全员群就已被禁言。目前留下的 300 多位员工，也是去年 11 月大裁员后剩余的人员，而 这家公司的下滑趋势，其实早在去年 4 月份就已显现。 当时 B 集团纪委收到了一封举报信，信中指明 A 公司一位年薪近百万的销售存在简历造假问题。集团大老板得知此事后十分震怒，当场拍了桌子要求彻查。这 一查不要紧，竟暴露出 A 公司财务方面的大问题，导致 A 公司彻底失去了集团大老板的信任。从那时起，A 公司的公章和包括审批付款在内的所有权限，都被 集团收回。 想当年 B 集团老大对 A 公司负责人乙可算是 ...

Core Insights - The article discusses various advanced directions in autonomous driving research, emphasizing the importance of deep learning and traditional methods for different academic backgrounds [2][3]. Group 1: Research Directions - Key areas of focus include VLA, end-to-end learning, reinforcement learning, 3DGS, and world models, which are recommended for students in computer science and automation [2]. - For mechanical and vehicle engineering students, traditional methods like PnC and 3DGS are suggested due to their lower computational requirements and ease of entry [2]. Group 2: Paper Guidance Services - The article announces the launch of a paper guidance service that covers various topics such as end-to-end learning, multi-sensor fusion, and trajectory prediction [3][6]. - The service includes support for topic selection, full process guidance, and experimental assistance [6]. Group 3: Publication Success - The guidance service has a high acceptance rate for papers submitted to top conferences and journals, including CVPR, AAAI, and ICLR [7]. - The article highlights the range of publication venues, including CCF-A, CCF-B, and various SCI categories [10].