3 citations · 6 across the 5 of their papers we have counts for
5 papers
Speed-up of Vision Transformer Models by Attention-aware Token Filtering
Takahiro Naruko, Hiroaki Akutsu
Vision Transformer (ViT) models have made breakthroughs in image embedding extraction, which provide state-of-the-art performance in tasks such as zero-shot image classification. H…
Universal Deep Image Compression via Content-Adaptive Optimization with Adapters
Koki Tsubota, Hiroaki Akutsu, Kiyoharu Aizawa
Deep image compression performs better than conventional codecs, such as JPEG, on natural images. However, deep image compression is learning-based and encounters a problem: the co…
Evaluating the Stability of Deep Image Quality Assessment With Respect to Image Scaling
Koki Tsubota, Hiroaki Akutsu, Kiyoharu Aizawa
Image quality assessment (IQA) is a fundamental metric for image processing tasks (e.g., compression). With full-reference IQAs, traditional IQAs, such as PSNR and SSIM, have been…
NTIRE 2021 Challenge on Perceptual Image Quality Assessment
Jinjin Gu, Haoming Cai, Chao Dong +47
This paper reports on the NTIRE 2021 challenge on perceptual image quality assessment (IQA), held in conjunction with the New Trends in Image Restoration and Enhancement workshop (…
Channel-Level Variable Quantization Network for Deep Image Compression
Zhisheng Zhong, Hiroaki Akutsu, Kiyoharu Aizawa
Deep image compression systems mainly contain four components: encoder, quantizer, entropy model, and decoder. To optimize these four components, a joint rate-distortion framework…