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Open nowPosted 267 days ago

3D虚拟人算法

n8r2cr07gk/index99 open roles

Where
Hangzhou, Zhejiang, Chinese Mainland
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Your applicationOpen now3D虚拟人算法n8r2cr07gk/index · Hangzhou, Zhejiang, Chinese Mainland

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The clock on this job

Early applications get read.

11.5% of postings close within 7 days. Measured by our own scanner across the market. n8r2cr07gk/index postings stay open a median of 1 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.5%7 days
  4. 18.1%14 days
  5. 35.6%30 days
  6. 44.6%60 days
This job: posted 267 days ago

n8r2cr07gk/index median: 1 days open

The posting

岗位职责： 核心算法研发：负责人体动作识别、姿态估计、关键点检测（2D/3D）算法的设计、开发与优化，重点攻克复杂场景下（如遮挡、快速动作、多人体交互）的姿态捕捉精度与鲁棒性问题，输出可落地的算法方案。 Mesh技术融合应用：结合3D Mesh建模技术，实现人体关键点与Mesh模型的精准绑定、动作驱动及形变优化，确保虚拟人动作的自然度与真实性，衔接Mesh拓扑优化、骨骼蒙皮等技术环节。 算法落地与迭代：将研发的姿态识别、动作捕捉算法与Mesh驱动流程集成，适配虚拟人直播、互动娱乐、数字孪生等业务场景，优化算法实时性与资源占用，解决工程化落地中的技术瓶颈。 技术调研与创新：跟踪国内外人体姿态估计、动作识别、3D Mesh生成与驱动领域的前沿技术（如基于Transformer的姿态模型、神经辐射场与Mesh结合方案），结合业务需求探索技术创新点，提升产品核心竞争力。 跨团队协作：与3D建模、虚拟人开发、前端/后端工程师协作，明确算法接口规范，推动姿态识别、Mesh驱动全链路的高效协同，保障虚拟人产品的动作表现效果。 算法效果验证与调优：构建算法测试数据集与评估指标，针对实际业务场景中的问题（如动作延迟、姿态偏差、Mesh形变异常）进行快速迭代调优，输出标准化的技术文档。

任职要求： 核心技能 本科及以上学历，计算机科学、自动化、电子信息、人工智能等相关专业，3年及以上人体动作识别、姿态估计、关键点检测领域算法研发经验，有虚拟人相关项目经验者优先。 精通人体姿态估计（2D/3D）、关键点检测核心算法（如HRNet、ViTPose、MediaPipe等），熟悉动作识别常用模型（如3D CNN、RNN、Transformer系列），能独立完成算法设计、训练与优化。 掌握3D Mesh相关技术栈，熟悉Mesh建模、拓扑优化、骨骼绑定、蒙皮权重计算等流程，了解主流Mesh处理工具（如Maya、Blender）或开源库（如Trimesh、PyMesh），能实现关键点与Mesh模型的精准联动。 熟练使用深度学习框架（TensorFlow/PyTorch），具备扎实的图像处理、计算机视觉、机器学习理论基础，能应对复杂场景下的算法鲁棒性优化问题。 熟悉C/C++/Python编程语言，具备良好的工程化能力，能将算法高效集成到实际业务系统，有实时性算法落地经验（如帧率优化、资源占用控制）者优先。 加分项 有动捕数据与Mesh驱动融合、虚拟人实时动作生成项目经验，或参与过数字人、元宇宙相关产品研发。 熟悉神经渲染（NeRF）、参数化人体模型（如SMPL、SMPL-X）与Mesh结合的技术方案，有相关算法实践经验。 了解直播互动、VR/AR、数字孪生等业务场景，能结合场景特性优化算法方案。 在顶会（CVPR、ICCV、ECCV）或核心期刊发表过人体姿态识别、3D Mesh相关论文，或有开源项目、竞赛获奖经历。 具备良好的问题分析能力、跨团队沟通能力，有复杂项目统筹或技术攻坚经验

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