Presentation
Auto-ISP: An Efficient Real-Time Automatic Hyperparameter Optimization Framework for ISP Hardware System
DescriptionImage Signal Processor (ISP) is widely used in intelligent edge devices across various scenarios. The intricate and time-consuming tuning process demands substantial expertise. Current AI-based auto-tuning operates discretely offline, relying on predefined scenes with human intervention, leading to inconvenient manipulation, with potentially fatal impacts on downstream tasks in unforeseen scenes. We propose a real-time automatic hyperparameter optimization ISP hardware system to address real-world scenarios. Our design features a tri-step framework and a hardware accelerator, demonstrating superior performance in human and computer vision tasks, even in real-time unforeseen scenes. Experiments showcase its practicality, achieving 1080P@75FPS/240FPS in FPGA/ASIC, respectively.
Event Type
Research Manuscript
TimeWednesday, June 2611:45am - 12:00pm PDT
Location3008, 3rd Floor
AI
Design
AI/ML System and Platform Design