MM's Journal of Technology

中文 English In May, I ran a small experiment. In my spare time, I mainly pair programmed with DeepSeek V4 Pro and built a 3D geometry processing application. During the last few days, Codex helped me with cleanup, refactoring, and final organization. Throughout the whole process, I basically only wrote requirements, made design decisions, reviewed results, and accepted or rejected behavior. I did not directly hand-write the business logic. The project is called 3D Claw, and the code is open ...

中文 English 五月份我做了一个小实验：在业余时间里，主要和 DeepSeek V4 Pro 结对编程，做出了一个 3D 几何处理软件。后面几天又让 Codex 帮我兜底重构和整理。整个过程中，我基本只提需求、做设计判断、审阅结果和验收行为，没有直接手写业务代码。 这个项目叫 3D Claw，代码已经开源： https://github.com/tangtangtang1995/3D-Claw 这篇文章不是想证明 AI 已经能替代程序员，也不是想包装什么神奇的一键开发流程。我更想记录的是：当一个有一定工程经验的人真正把 AI 当成结对编程对象时，哪些事情变得很快，哪些事情依然绕不开，以及这个过程中最考验人的地方到底是什么。 我的编程背景 如果把大一大二在机器人队里参与电调、检测羽毛球轨迹那种补丁式开发也算上，我大概有十多年 C/C++ 编程经验。后来读研做算法，主要语言变成了 Python 和 MATLAB。工作之后因为项目落地，又重新补了一些底层、工程和混合编程的知识。 我一直觉得语言之间是相通的。熟悉了 C++ 这种“高级汇编”之后，再上手解释型语言通常不会太慢。 ...

I came up with an absolutely brilliant idea. Unfortunately, I do not have many tokens left today, so I will stop writing for now. ------Cyber Fermat Before We Begin DeepSeek V4 Pro’s coding ability is not really the same thing for every person. A thousand users will raise a thousand little whales. Everyone uses different languages, tasks, requirements, domains, and prompts. Of course, one job of an agent is to smooth out those differences as much as possible, but the differences still exist, a ...

中文版 Prologue This is a document I wrote last year (2025). It started because a few game developer friends were super interested in 3D generation. At the time, they were already using text-to-image tools in their workflows to generate various character models, props, and even 3DGS-based scene assets. They really wanted to understand how these productivity-liberating tools worked under the hood, so I hastily scribbled down this document for them, (hopefully) explaining things in plain English. It ...

中文版 Low-poly Reconstruction, which we might also call Vectorized 3D Reconstruction or Structured Reconstruction, centers on extracting structural, topological, and semantic information from scattered, unordered, and redundant dense point clouds or triangular meshes. Its core objective is to represent a model using points, lines, and planes (and their combinations) defined by analytical mathematical equations. When the final model is completely composed of compact Planar Polygons, we have achieve ...

中文版 In the world of digital imaging, the classic photo of “Lenna” in her feathered hat serves as the universal benchmark for image processing (for her story, see Lenna 97 (NSFW)). If we were to find its authoritative counterpart in the 3D domain, the Stanford Bunny is undoubtedly the one. It even has its own Wikipedia page. On Reddit, it’s common to see users rendering or 3D-printing the model, with the comments section inevitably bringing up Lenna (haha). It was also inducted into the 3D Sample ...

写在前面 图生三维大概有五个阶段： 第一阶段是古法时期(传统的多视图几何)[2010-2020]：使用SFM, MVS从图片中恢复相机位姿，然后生成稠密点云，现在已经非常的成熟，有colmap, openmvg等非常优秀的开源工具，还有视觉slam等一系列的工作(如果这种也算重建的话)； 第二阶段是深度学习时期[2018-2021]：利用大量的二维数据进行单目深度估计，以及使用gan模型，进行3d gan生成的尝试； 第三阶段是神经渲染时期[2020-2023]：利用Nerf的可微分体渲染对单个场景进行过拟合，输出神经辐射场，随后也衍生出了 3DGS 等更高效的显式/混合表达； 第四个阶段是2D 先验（Diffusion）时期[2022-2024]：二维扩散模型的大火让研究者发现了从二维知识蒸馏监督三维生成的可行性，除了三渲二，还能“二训三”（代表就是引入 SDS 损失的 DreamFusion）； 第五阶段是 3D 原生大模型（LRM/DiT）时期[2023-至今]：随着 3D VAE 的验证、DiT 架构的完善、海量 3D 数据的积累以及 Triplane 等高效结构的广泛应用，直 ...

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TODO

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