10 papers
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…
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…
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…
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…
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…
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…
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…