Core Viewpoint - VAST has launched new 3D generative models, TripoSG and TripoSF, which have set new state-of-the-art (SOTA) benchmarks in the open-source 3D generation field, showcasing significant advancements in quality, detail, and performance [6][8][12]. Group 1: Model Launch and Features - TripoSG is a foundational 3D generative model that has achieved a new SOTA in open-source 3D generation, emphasizing quality, detail, and fidelity [14][16]. - TripoSF, currently in its first phase of open-source release, has proven its capabilities by surpassing existing open-source and closed-source methods, also achieving a new SOTA [8][16]. - VAST plans to continue its open-source initiative for a month, releasing new projects weekly, including various advanced 3D models and techniques [10][66]. Group 2: Technical Innovations - TripoSG incorporates several key design innovations, including the application of a Rectified Flow-based Transformer architecture for 3D shape generation, which offers a more stable and efficient training process compared to traditional diffusion models [21][22]. - The model is the first in the 3D domain to utilize a Mixture of Experts (MoE) Transformer, enhancing feature fusion and allowing for efficient integration of global and local image features [23][24]. - VAST has developed a high-quality Variational Autoencoder (VAE) with innovative geometric supervision, utilizing Signed Distance Functions (SDFs) for improved precision in geometric representation [28][30]. Group 3: Performance Metrics - TripoSG has been evaluated using Normal-FID and other quantitative metrics, demonstrating superior performance in semantic consistency and the ability to accurately reflect the input image's semantic content [34][35]. - TripoSF has achieved approximately 82% reduction in Chamfer Distance and about 88% improvement in F-score across multiple benchmark tests, indicating its high-quality output [57]. Group 4: Future Developments - VAST's upcoming projects include a comprehensive suite of 3D generation technologies, with plans for models focused on 3D component completion and general 3D model binding generation [66][67]. - The final week of the open-source month will feature cutting-edge explorations in 3D generation, including geometric refinement models and interactive sketch-to-3D models [68][69]. Group 5: Industry Impact - VAST is recognized as a leading company in the 3D generative model space, actively contributing to the open-source community and pushing the boundaries of 3D content creation technology [80][87]. - The company aims to democratize 3D content creation, making it accessible to everyone by the end of 2025, aligning with the broader trend of advancing AIGC technologies [85][86].

高校，创新源头。 作者 I 刘博 陈晓 报道 I 投资界PEdaily 一群年轻面孔闯入创投圈。 投资界获悉，3D生成大模型公司影眸科技完成数千万美元 A 轮融资，由美团龙珠、字节 跳动领投，老股东红杉中国种子基金及奇绩创坛持续跟投。令人意外的是，公司团队平均 年龄只有2 4 岁。 这是一个孵化自上海科技大学的创业项目——2 0 2 0年，吴迪、张启煊、张龙文、曾初啸 等人创立影眸科技，团队与上科大共同提出的可控 3D 原生 DiT生成框架 CLAY 与 3D 服装生成框架 Dr e ssCod e，均获计算机图形学顶会 ACM SIGGRAPH 2 0 24 最佳论文提 名，被认为是新一代 3D 生成基础框架。 "现在我们经常跑上科大蹲项目。"此前一家知名早期投资机构的分享引起我们的注意。 不同于清华、上海交大、哈工大等传统名校，上科大乍听略显陌生，成立仅仅十余年，殊 不知已经累计孵化4 0多家科创企业。如此一幕，堪称中国科技成果转化大潮的一缕写 照。 团队平均24岁 刚刚，美团字节联手投了 影眸科技的故事，始于上科大的一间实验室。 出生于19 9 7年，吴迪在20 1 5年进入上科大学习，是该校招的第二届 ...