Document detail
ID
oai:arXiv.org:2405.11894
Topic
Computer Science - Computer Vision... Electrical Engineering and Systems...Author
Shindo, Takahiro Tatsumi, Yui Watanabe, Taiju Watanabe, HiroshiCategory
Computer Science
Year
2024
listing date
6/19/2024
Keywords
vision images method imageAbstract
Scalable image coding for both humans and machines is a technique that has gained a lot of attention recently.
This technology enables the hierarchical decoding of images for human vision and image recognition models.
It is a highly effective method when images need to serve both purposes.
However, no research has yet incorporated the post-processing commonly used in popular image compression schemes into scalable image coding method for humans and machines.
In this paper, we propose a method to enhance the quality of decoded images for humans by integrating post-processing into scalable coding scheme.
Experimental results show that the post-processing improves compression performance.
Furthermore, the effectiveness of the proposed method is validated through comparisons with traditional methods.
Shindo, Takahiro,Tatsumi, Yui,Watanabe, Taiju,Watanabe, Hiroshi, 2024, Refining Coded Image in Human Vision Layer Using CNN-Based Post-Processing
Distilling Implicit Multimodal Knowledge into LLMs for Zero-Resource Dialogue Generation
generation knowledge zero-resource dialogue
