@inproceedings{
yan2024taskoriented,
title={Task-Oriented Multi-Bitstream Optimization for Image Compression and Transmission via Optimal Transport},
author={Sa Yan and Nuowen Kan and Chenglin Li and Wenrui Dai and Junni Zou and Hongkai Xiong},
booktitle={ACM Multimedia 2024},
year={2024},
url={https://openreview.net/forum?id=wOx1VBzF8k}
}
Image compression for machine vision exhibits various rate-accuracy performance across different downstream tasks and content types. 
An efficient utilization of constrained network resource for achieving an optimal overall task performance has thus recently attracted a growing attention. In this paper, we propose Tombo, a task-oriented image compression and transmission framework that efficiently identifies the optimal encoding bitrate and routing scheme for multiple image bitstreams delivered simultaneously for different downstream tasks. Specifically, we study the characteristics of image rate-accuracy performance for different machine vision tasks, and formulate the task-oriented joint bitrate and routing optimization problem for multi-bitstreams as a multi-commodity network flow problem with the time-expanded network modeling. To ensure consistency between the encoding bitrate and routing optimization, we also propose an augmented network that incorporates the encoding bitrate variables into the routing variables. To improve computational efficiency, we further convert the original optimization problem to a multi-marginal optimal transport problem, and adopt a Sinkhorn iteration-based algorithm to quickly obtain the near-optimal solution. Finally, we adapt Tombo to efficiently deal with the dynamic network scenario where link capacities may fluctuate over time. Empirical evaluations on three typical machine vision tasks and four real-world network topologies demonstrate that Tombo achieves a comparable performance to the optimal one solved by the off-the-shelf solver Gurobi, with a $5\times \sim 114\times$ speedup.
Task-Oriented Multi-Bitstream Optimization for Image Compression and Transmission via Optimal Transport
Sa Yan Nuowen Kan Chenglin Li Wenrui Dai Junni Zou Hongkai Xiong