FAST: A Framework to Accelerate Super-Resolution Processing on Compressed Videos
© 2017 IEEE. State-of-the-art super-resolution (SR) algorithms require significant computational resources to achieve real-time throughput (e.g., 60Mpixels/s for HD video). This paper introduces FAST (Free Adaptive Super-resolution via Transfer), a framework to accelerate any SR algorithm applied to...
Main Authors: | Zhang, Zhengdong, Sze, Vivienne |
---|---|
Other Authors: | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science |
Format: | Article |
Language: | English |
Published: |
IEEE
2021
|
Online Access: | https://hdl.handle.net/1721.1/137100 |
Similar Items
-
Lightweight Video Super-Resolution for Compressed Video
by: Ilhwan Kwon, et al.
Published: (2023-01-01) -
Edge-Oriented Compressed Video Super-Resolution
by: Zheng Wang, et al.
Published: (2023-12-01) -
A 58.6mW 30fps Real-Time Programmable Multi-Object Detection Accelerator with Deformable Parts Models on Full HD 1920×1080 Videos
by: Sze, Vivienne, et al.
Published: (2017) -
Fast On-Device Learning Framework for Single-Image Super-Resolution
by: Seok Hee Lee, et al.
Published: (2024-01-01) -
A Super-Resolution-Based Feature Map Compression for Machine-Oriented Video Coding
by: Jung-Heum Kang, et al.
Published: (2023-01-01)