Most video compression methods aim to improve the decoded video visual quality, instead
of particularly guaranteeing the semantic-completeness, which deteriorates downstream …

Video compression is indispensable to most video analysis systems. Despite saving the
transportation bandwidth, it also deteriorates downstream video understanding tasks …

Image compression techniques typically focus on compressing rectangular images for
human consumption, however, resulting in transmitting redundant content for downstream …

Recently, more and more images are compressed and sent to the back-end devices for the
machine analysis tasks~(\textit {eg,} object detection) instead of being purely watched by …

Image coding for machines (ICM) aims to compress images to support downstream AI
analysis instead of human perception. For ICM, developing a unified codec to reduce …

Prior research on deep video compression (DVC) for machine tasks typically necessitates
training a unique codec for each specific task mandating a dedicated decoder per task. In …

Unsupervised Person Re-identification (U-ReID) with pseudo labeling recently reaches a
competitive performance compared to fully-supervised ReID methods based on modern …

As image recognition models become more prevalent, scalable coding methods for
machines and humans gain more importance. Applications of image recognition models …

Traditional image coding standards are typically optimized with a focus on human
perception, which conflicts with the fact that most of the images are now analyzed by …

Compression technology is essential for efficient image transmission and storage. With the
rapid advances in deep learning, images are beginning to be used for image recognition as …