most citedLearned Image Compression with Mixed Transformer-CNN Architectures

12 citations · 13 across the 5 of their papers we have counts for

collaborators

5 papers

eess.IV202312 cited

Learned Image Compression with Mixed Transformer-CNN Architectures

Jinming Liu, Heming Sun, Jiro Katto

Learned image compression (LIC) methods have exhibited promising progress and superior rate-distortion performance compared with classical image compression standards. Most existin…

cs.CV20231 cited

Multistage Spatial Context Models for Learned Image Compression

Fangzheng Lin, Heming Sun, Jinming Liu +1

Recent state-of-the-art Learned Image Compression methods feature spatial context models, achieving great rate-distortion improvements over hyperprior methods. However, the autoreg…

cs.CV2022

Semantic Segmentation in Learned Compressed Domain

Jinming Liu, Heming Sun, Jiro Katto

Most machine vision tasks (e.g., semantic segmentation) are based on images encoded and decoded by image compression algorithms (e.g., JPEG). However, these decoded images in the p…

eess.IV2022

Learned Lossless Image Compression With Combined Autoregressive Models And Attention Modules

Ran Wang, Jinming Liu, Heming Sun +1

Lossless image compression is an essential research field in image compression. Recently, learning-based image compression methods achieved impressive performance compared with tra…

eess.IV2022

Streaming-capable High-performance Architecture of Learned Image Compression Codecs

Fangzheng Lin, Heming Sun, Jiro Katto

Learned image compression allows achieving state-of-the-art accuracy and compression ratios, but their relatively slow runtime performance limits their usage. While previous attemp…