7 papers
Improving Image Coding for Machines through Optimizing Encoder via Auxiliary Loss
Kei Iino, Shunsuke Akamatsu, Hiroshi Watanabe +3
Image coding for machines (ICM) aims to compress images for machine analysis using recognition models rather than human vision. Hence, in ICM, it is important for the encoder to re…
Training-Free Adaptive Quantization for Variable Rate Image Coding for Machines
Yui Tatsumi, Ziyue Zeng, Hiroshi Watanabe
Image Coding for Machines (ICM) has become increasingly important with the rapid integration of computer vision technology into real-world applications. However, most neural networ…
Explicit Residual-Based Scalable Image Coding for Humans and Machines
Yui Tatsumi, Ziyue Zeng, Hiroshi Watanabe
Scalable image compression is a technique that progressively reconstructs multiple versions of an image for different requirements. In recent years, images have increasingly been c…
Seed Selection for Human-Oriented Image Reconstruction via Guided Diffusion
Yui Tatsumi, Ziyue Zeng, Hiroshi Watanabe
Conventional methods for scalable image coding for humans and machines require the transmission of additional information to achieve scalability. A recent diffusion-based approach…
Classification in Japanese Sign Language Based on Dynamic Facial Expressions
Yui Tatsumi, Shoko Tanaka, Shunsuke Akamatsu +2
Sign language is a visual language expressed through hand movements and non-manual markers. Non-manual markers include facial expressions and head movements. These expressions vary…
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…