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JD Tech Talk
JD Tech Talk
Apr 22, 2025 · Artificial Intelligence

End-to-End 3D Spatial Video Generation via Monocular Depth Estimation, Novel View Synthesis, and MV-HEVC Encoding

Leveraging AI-driven monocular depth estimation, novel view synthesis, and MV‑HEVC encoding, the JD Retail Content R&D team presents an end‑to‑end pipeline that converts 2D video assets into high‑quality immersive 3D spatial videos, introduces the large‑scale StereoV1K dataset, and demonstrates superior performance over existing methods.

3D video generationAIGCMV-HEVC
0 likes · 22 min read
End-to-End 3D Spatial Video Generation via Monocular Depth Estimation, Novel View Synthesis, and MV-HEVC Encoding
Kuaishou Tech
Kuaishou Tech
Jul 23, 2021 · Artificial Intelligence

Real-time Single-image 3D Photo Generation on Mobile Devices Using Deep Learning

The article presents a mobile‑first solution that converts a single RGB photograph into an interactive 3D photo by combining learning‑based monocular depth estimation, multi‑task image‑and‑depth restoration, face‑specific refinement, and a custom KwaiNN inference engine to achieve real‑time rendering on all smartphone models without requiring depth sensors.

3D PhotoARKwaiNN
0 likes · 16 min read
Real-time Single-image 3D Photo Generation on Mobile Devices Using Deep Learning
Kuaishou Large Model
Kuaishou Large Model
Jul 23, 2021 · Artificial Intelligence

How Kuaishou’s Y‑Tech Achieved Real‑Time 3D Photo Rendering on Any Smartphone

The article details Kuaishou Y‑Tech’s end‑to‑end solution for converting a single RGB image into an interactive 3D photo on mobile devices, covering depth estimation, image‑inpainting, custom KwaiNN inference, and real‑time 3D rendering techniques that run on all smartphone models without depth sensors.

3D PhotoImage InpaintingKwaiNN
0 likes · 17 min read
How Kuaishou’s Y‑Tech Achieved Real‑Time 3D Photo Rendering on Any Smartphone
Kuaishou Large Model
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 mechanismcomputer visiondeep learning
0 likes · 14 min read
How Kuaishou’s Y‑Tech Advances Monocular Depth Estimation for Mobile AR