Augmented Reality Media Enhancement Suite

Problem Statement

A digital experience brand needed scalable media preparation for AR campaigns, including fast background removal from product photos and dynamic video enhancement with contextual overlays.

Technical Architecture

We built a Python computer-vision pipeline using segmentation and enhancement models, then integrated the output with WebXR/Three.js rendering services. Background removal, object cut-outs, and component overlays were processed through asynchronous queues with Redis-backed job orchestration.

Technology Stack: Python, OpenCV, PyTorch, ONNX Runtime, WebXR, Three.js, Redis, AWS

Business Transformation

Creative and campaign teams could generate AR-ready assets faster, with consistent output quality and significantly less manual editing effort.

Quantifiable Outcomes

• 69% reduction in manual photo background editing time
• 46% faster turnaround for AR-ready campaign assets
• 2.2x increase in interactive media output per sprint