编辑丨 量子位 点击下方 卡片 ，关注" 具身智能之心 "公众号 >> 点击进入→ 具身 智能之心 技术交流群 更多干货，欢迎加入国内首个具身智能全栈学习社区 ： 具身智能之心知识星球 (戳我) ， 这里包含所有你想要的。 刚刚，备受瞩目的ICCV 2025，在美国夏威夷正式"开奖"！ 好家伙，在提交论文的作者里，中国直接占了半壁江山，不多不少占比50%。 各个奖项也是重中之重捷报频传，现场更是人山人海……好在前方参会的"詹姆斯邦迪" ( 小红书博主，欢迎大家去 follow) ，第一时间分享了最 新进展。 让我们一起膜拜看看顶会荣耀，今年花落谁家？ 最佳论文奖（马尔奖） ： Generating Physically Stable and Buildable Brick Structures from Text（从文本生成物理稳定且可搭建的积木结构）。 △ 图源小红书博主：@詹姆斯邦迪 最佳学生论文奖 ： FlowEdit: Inversion-Free Text-Based Editing Using Pre-Trained Flow Models（基于预训练流模型的无反演文本编辑方法） 。 △ 图源小红 ...

编辑丨 机器之心 点击下方 卡片 ，关注" 具身智能之心 "公众号 >> 点击进入→ 具身 智能之心 技术交流群 更多干货，欢迎加入国内首个具身智能全栈学习社区 ： 具身智能之心知识星球 (戳我) ， 这里包含所有你想要的。 ICCV 是全球计算机视觉三大顶会之一，每两年举办一次，今年的会议在美国夏威夷举行。数据显示，今年大会共收到了 11239 份有效投稿，程序委员会推荐录用 2699 篇论文，最终录用率为 24%，相比上一届论文数量又有大幅增长。 最佳论文 最佳论文奖是来自卡耐基梅隆大学，AI 领域知名青年学者朱俊彦带领团队的论文《Generating Physically Stable and Buildable Brick Structures from Text》。 朱俊彦，清华大学校友，卡耐基梅隆大学计算机科学学院助理教授，前 Adobe 研究科学家。主要研究方向是计算机视觉、图形学、计算摄影和生成模型。 10 月 22 日凌晨，国际计算机视觉大会 ICCV（IEEE International Conference on Computer Vision）揭幕了本年度最佳论文等奖项。 来自卡耐基梅 ...

Core Points - The ICCV 2025 conference in Hawaii highlighted significant contributions from Chinese researchers, who accounted for 50% of the paper submissions [1] - Various prestigious awards were announced, showcasing advancements in computer vision research [3] Award Highlights - Best Paper Award (Marr Prize): "Generating Physically Stable and Buildable Brick Structures from Text" introduced BRICKGPT, a model that generates stable brick structures based on text prompts, utilizing a dataset of over 47,000 structures [4][24][26] - Best Student Paper Award: "FlowEdit: Inversion-Free Text-Based Editing Using Pre-Trained Flow Models" proposed a method for image editing without inversion, achieving state-of-the-art results [6][39][40] - Best Paper Honorary Mention: "Spatially-Varying Autofocus" developed a technique for dynamic depth adjustment in imaging, enhancing focus clarity across scenes [7][42][44] - Best Student Paper Honorary Mention: "RayZer: A Self-supervised Large View Synthesis Model" demonstrated 3D perception capabilities using uncalibrated images [9][47][49] Special Awards - Helmholtz Prize: Awarded to "Fast R-CNN" for its efficient object detection capabilities, significantly improving training and testing speeds [10][52][54] - Another Helmholtz Prize was given for research on rectified activation functions, achieving performance surpassing human-level accuracy on ImageNet [10][59][60] - Evelyn Erham Award: Recognized teams for their contributions to 3D modeling and visual question answering [12][63][68] - Distinguished Researcher Award: David Forsyth and Michal Irani were honored for their impactful work in computer vision [14][73][76] - Azriel Rosenfeld Lifetime Achievement Award: Rama Chellappa was recognized for his extensive contributions to the field [16][79] Research Contributions - The BRICKGPT model was developed to generate physically stable structures, utilizing a large dataset and innovative mechanisms for stability [24][26] - FlowEdit's approach allows for seamless image editing across different model architectures, enhancing flexibility in applications [39][40] - The spatially-varying autofocus technique improves image clarity by dynamically adjusting focus based on scene depth [42][44] - RayZer's self-supervised learning approach enables 3D scene reconstruction without the need for calibrated camera data [47][49] Conclusion - The ICCV 2025 conference showcased groundbreaking research and innovations in computer vision, with significant contributions from various teams and individuals, particularly highlighting the achievements of Chinese researchers [1][3]

10 月 22 日凌晨，国际计算机视觉大会 ICCV（IEEE International Conference on Computer Vision）揭幕了本年度最佳论文等奖项。 最佳论文奖是来自卡耐基梅隆大学，AI 领域知名青年学者朱俊彦带领团队的论文《Generating Physically Stable and Buildable Brick Structures from Text》。 机器之心编辑部 来自卡耐基梅隆大学（CMU）的研究获得了最佳论文奖，以色列理工学院（Technion）的研究获得最佳学生论文奖。 机器之心报道 ICCV 是全球计算机视觉三大顶会之一，每两年举办一次，今年的会议在美国夏威夷举行。数据显示，今年大会共收到了 11239 份有效投稿，程序委员会推荐录用 2699 篇论文，最终录用率为 24%，相比上一届论文数量又有大幅增长。 最佳论文 朱俊彦，清华大学校友，卡耐基梅隆大学计算机科学学院助理教授，前 Adobe 研究科学家。主要研究方向是计算机视觉、图形学、计算摄影和生成模型。 论文标题：Generating Physically Stable and Buildable ...