5 papers
Guided Diffusion for the Extension of Machine Vision to Human Visual Perception
Takahiro Shindo, Yui Tatsumi, Taiju Watanabe +1
Image compression technology eliminates redundant information to enable efficient transmission and storage of images, serving both machine vision and human visual perception. For y…
Delta-ICM: Entropy Modeling with Delta Function for Learned Image Compression
Takahiro Shindo, Taiju Watanabe, Yui Tatsumi +1
Image Coding for Machines (ICM) is becoming more important as research in computer vision progresses. ICM is a vital research field that pursues the use of images for image recogni…
Refining Coded Image in Human Vision Layer Using CNN-Based Post-Processing
Takahiro Shindo, Yui Tatsumi, Taiju Watanabe +1
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…
Scalable Image Coding for Humans and Machines Using Feature Fusion Network
Takahiro Shindo, Taiju Watanabe, Yui Tatsumi +1
As image recognition models become more prevalent, scalable coding methods for machines and humans gain more importance. Applications of image recognition models include traffic mo…
Image Coding for Machines with Edge Information Learning Using Segment Anything
Takahiro Shindo, Kein Yamada, Taiju Watanabe +1
Image Coding for Machines (ICM) is an image compression technique for image recognition. This technique is essential due to the growing demand for image recognition AI. In this pap…