ecommerce_ops · ecommerce · workflow
Google uses Veo generative AI to create shoppable 3D product visualizations from 2D product images for Google Shopping
Online shopping cannot replicate the tactile, hands-on experience of physical stores, and creating high-quality 3D product visualization tools at scale has been costly and time-consuming for businesses.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Product images submitted
As few as three product images are provided as input to generate a shoppable 3D visualization.
Tools used
VeoNeural Radiance Fields (NeRF)view-conditioned diffusion model
Outcome
The Veo-based third-generation approach generates interactive 3D views from as few as three product images, generalizes across furniture, apparel, and electronics, and is already deployed on Google Shopping without requiring precise camera pose estimation.
What failed first
The first-generation NeRF approach suffered from noisy camera pose signals and struggled with thin-structured products like sandals and heels; both early approaches required estimating precise camera poses from sparse images.
Results
Volumethree
Running since2022
Grounding & classification
Source type: technical build writeup
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computer visioncontent generationproduct catalogmetric backednamed customerproduction runtime claimedsource backedtools describedworkflow describedecommercesoftwareaccuracy improvementtechnical build writeupecommerce ops