  Image compression techniques typically focus on compressing rectangular
images for human consumption, however, resulting in transmitting redundant
content for downstream applications. To overcome this limitation, some previous
works propose to semantically structure the bitstream, which can meet specific
application requirements by selective transmission and reconstruction.
Nevertheless, they divide the input image into multiple rectangular regions
according to semantics and ignore avoiding information interaction among them,
causing waste of bitrate and distorted reconstruction of region boundaries. In
this paper, we propose to decouple an image into multiple groups with irregular
shapes based on a customized group mask and compress them independently. Our
group mask describes the image at a finer granularity, enabling significant
bitrate saving by reducing the transmission of redundant content. Moreover, to
ensure the fidelity of selective reconstruction, this paper proposes the
concept of group-independent transform that maintain the independence among
distinct groups. And we instantiate it by the proposed Group-Independent
Swin-Block (GI Swin-Block). Experimental results demonstrate that our framework
structures the bitstream with negligible cost, and exhibits superior
performance on both visual quality and intelligent task supporting.
