腾讯《穿越火线:虹》技术美术(渲染)
社招全职3年以上CFH-手游APP设计地点:深圳状态:招聘
任职要求
1.3年以上游戏项目经验;有至少一个成功上线项目 ,同时具备端游手游经验者优先; 2.熟悉色彩和物理灯光相关知识,了解PBR理论; 3.具备图形学基础,及高等数学知识; 熟悉实时渲染管线; 4.熟练掌握GLSL, HLSL, CG等至少一门Shader编程语言; 5.熟悉OpenGL ES…
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工作职责
1.和美术人员,引擎程序员一起设计渲染方案,编写Shader,实现美术效果; 2.为场景和角色美术搭建Lookdev环境,确保美术资产在不同光照环境下的效果表现; 3.研究业内新图形技术(Postprocess、Shader、VFX等)并结合项目需求,推动方案整合; 4.创建可视化原型来验证艺术方向和效果,并推动技术方案设计; 5.提供开发过程中和美术制作相关的解决方案; 6.优化美术pipeline,并开发工具提高美术工作流效率支持美术和开发团队,解决生产中遇到的问题; 7.设计美术资源规范,确保引擎规范的执行; 8.编写并维护技术文档,向美术推广新工具和最佳实践; 9.面对紧张的交付节点,平衡产出效率和质量。
包括英文材料
Shader+
https://clauswilke.com/art/post/shaders
To the uninitiated, shader programming can appear like magic.
https://learnopengl.com/Getting-started/Shaders
A great resource to learn modern OpenGL aimed at beginners.
[英文] Shader Learning
https://shader-learning.com/
Shader Learning is a platform that helps you learn and enhance your shading skills by solving interactive problems.
https://www.youtube.com/watch?v=3mfvZ-mdtZQ
Shaders are an incredibly useful programming tool to have under your belt, especially for creative coding and generative art.
OpenGL+
https://www.youtube.com/watch?v=45MIykWJ-C4
Learn how to use OpenGL to create 2D and 3D vector graphics in this course.
https://www.youtube.com/watch?v=W3gAzLwfIP0&list=PLlrATfBNZ98foTJPJ_Ev03o2oq3-GGOS2
https://www.youtube.com/watch?v=XpBGwZNyUh0&list=PLPaoO-vpZnumdcb4tZc4x5Q-v7CkrQ6M-
ElasticSearch+
https://www.youtube.com/watch?v=a4HBKEda_F8
Learn about Elasticsearch with this comprehensive course designed for beginners, featuring both theoretical concepts and hands-on applications using Python (though applicable to any programming language). The course is structured in two parts: first covering essential Elasticsearch fundamentals including index management, document storage, text analysis, pipeline creation, search functionality, and advanced features like semantic search and embeddings; followed by a practical section where you'll build a real-world website using Elasticsearch as a search engine, working with the Astronomy Picture of the Day (APOD) dataset to implement features such as data cleaning pipelines, tokenization, pagination, and aggregations.
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