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Kuaishou Large Model

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Latest from Kuaishou Large Model

54 recent articles

Kuaishou Large Model

Dec 10, 2020 · Game Development

How PBR Transforms Mobile 3D Makeup: From Theory to Real‑World Apps

This article explores the fundamentals of Physically Based Rendering (PBR) for mobile devices, detailing key parameters such as albedo, metallic, roughness, and reflectance, and demonstrates their application in realistic 3D makeup effects like high‑gloss lipstick and water‑light eye shadow under both direct and indirect lighting.

3D MakeupPBRmobile rendering

0 likes · 14 min read

How PBR Transforms Mobile 3D Makeup: From Theory to Real‑World Apps

Kuaishou Large Model

Dec 3, 2020 · Artificial Intelligence

Kuaishou Y‑Tech’s Real‑Time, High‑Precision Facial & Body Keypoint Detection Explained

Y‑Tech’s in‑house keypoint detection system powers Kuaishou’s beauty and effect filters across live streaming, video creation, and editing by leveraging lightweight deep‑learning models, extensive multi‑scenario data collection, and specialized handling of occlusion, enabling real‑time, robust facial and body landmark tracking on diverse mobile devices.

beauty filterscomputer visiondeep learning

0 likes · 10 min read

Kuaishou Y‑Tech’s Real‑Time, High‑Precision Facial & Body Keypoint Detection Explained

Kuaishou Large Model

Oct 22, 2020 · Fundamentals

Why Deferred Rendering Beats Forward Rendering on Mobile GPUs – A Deep Dive

This article compares forward and deferred rendering techniques, analyzes their performance trade‑offs on mobile GPUs, explores tile‑based and hardware‑TBDR approaches, and presents a Metal‑based single‑pass deferred shading solution for modern mobile graphics pipelines.

GraphicsMetalMobile GPU

0 likes · 15 min read

Why Deferred Rendering Beats Forward Rendering on Mobile GPUs – A Deep Dive

Kuaishou Large Model

Oct 15, 2020 · Artificial Intelligence

How Kuaishou’s Y‑Tech Advances Monocular Depth Estimation for Mobile AR

This article reviews Kuashou Y‑Tech’s ECCV‑2020 paper on monocular depth estimation, detailing its novel GCB‑SAB network, new HC‑Depth dataset, specialized loss functions and edge‑aware training, and demonstrates superior performance on NYUv2, TUM and real‑world mobile AR applications.

Attention MechanismMobile ARcomputer vision

0 likes · 14 min read

How Kuaishou’s Y‑Tech Advances Monocular Depth Estimation for Mobile AR