3 papers
cs.CV2023
ConvNeXt-ChARM: ConvNeXt-based Transform for Efficient Neural Image Compression
Ahmed Ghorbel, Wassim Hamidouche, Luce Morin
Over the last few years, neural image compression has gained wide attention from research and industry, yielding promising end-to-end deep neural codecs outperforming their convent…
cs.CV2023
AICT: An Adaptive Image Compression Transformer
Ahmed Ghorbel, Wassim Hamidouche, Luce Morin
Motivated by the efficiency investigation of the Tranformer-based transform coding framework, namely SwinT-ChARM, we propose to enhance the latter, as first, with a more straightfo…
cs.CV2023
Joint Hierarchical Priors and Adaptive Spatial Resolution for Efficient Neural Image Compression
Ahmed Ghorbel, Wassim Hamidouche, Luce Morin
Recently, the performance of neural image compression (NIC) has steadily improved thanks to the last line of study, reaching or outperforming state-of-the-art conventional codecs.…