The ever-improving display capabilities of TVs, smartphones, or VR headsets foster the need for efficient upscaling solutions. While DL-based solutions usually obtain impressive results in terms of visual quality, they are often slow and not suited for real-time applications on mobile platforms. In this demonstration, we showcase Q-SRNet, our efficient single-image super-resolution architecture, which provides better accuracy-to-latency tradeoffs than existing neural architectures. We apply our architecture to gaming and show that our solution outperforms existing non-ML based approaches.
To further optimize on-device performance, we leverage the AI Model Efficiency Toolkit (AIMET)’s latest advances in low-bit quantization and obtain excellent accuracy with 4-bit quantization (W4A8). Q-SRNet produces 4k images at 4x upscaling and 200+ FPS on a Qualcomm® Reference Design phone powered by Snapdragon® 8 Gen 2 Mobile Platform.