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Found 4 papers, 1 papers with code
Fast and Accurate: Video Enhancement using Sparse Depth
This paper presents a general framework to build fast and accurate algorithms for video enhancement tasks such as super-resolution, deblurring, and denoising.
ISP4ML: Understanding the Role of Image Signal Processing in Efficient Deep Learning Vision Systems
In this work, we investigate the efficacy of the ISP in CNN classification tasks, and outline the system-level trade-offs between prediction accuracy and computational cost.
FixyNN: Efficient Hardware for Mobile Computer Vision via Transfer Learning
Over a suite of six datasets we trained models via transfer learning with an accuracy loss of $<1\%$ resulting in up to 11. 2 TOPS/W - nearly $2 \times$ more efficient than a conventional programmable CNN accelerator of the same area.
Energy Efficient Hardware for On-Device CNN Inference via Transfer Learning
On-device CNN inference for real-time computer vision applications can result in computational demands that far exceed the energy budgets of mobile devices.
