Elic: Efficient learned image compression with unevenly grouped space-channel contextual adaptive coding
Recently, learned image compression techniques have achieved remarkable performance,
even surpassing the best manually designed lossy image coders. They are promising to be …
even surpassing the best manually designed lossy image coders. They are promising to be …
Learned image compression using cross-component attention mechanism
Learned image compression methods have achieved satisfactory results in recent years.
However, existing methods are typically designed for RGB format, which are not suitable for …
However, existing methods are typically designed for RGB format, which are not suitable for …
End-to-end learning-based image compression with a decoupled framework
The autoregressive model has been widely used in learning-based image compression due
to its superior context modeling capability. However, its sequential processing nature also …
to its superior context modeling capability. However, its sequential processing nature also …
Boosting neural video codecs by exploiting hierarchical redundancy
In video compression, coding efficiency is improved by reusing pixels from previously
decoded frames via motion and residual compensation. We define two levels of hierarchical …
decoded frames via motion and residual compensation. We define two levels of hierarchical …
Deep video compression for P-frame in sub-sampled color spaces
In this paper, we propose a deep video compression method for P-frame in sub-sampled
color spaces regarding the YUV420, which has been widely adopted in many state-of-art …
color spaces regarding the YUV420, which has been widely adopted in many state-of-art …
End-to-end image compression via attention-guided information-preserving module
Deep learning-based end-to-end image compression has achieved significant compression
performance in recent years. However, current learning-based image compression methods …
performance in recent years. However, current learning-based image compression methods …
Practical learned lossless jpeg recompression with multi-level cross-channel entropy model in the dct domain
JPEG is a popular image compression method widely used by individuals, data center,
cloud storage and network filesystems. However, most recent progress on image …
cloud storage and network filesystems. However, most recent progress on image …
Graph Based Cross-Channel Transform for Color Image Compression
L Wang, Y Shi, J Wang, S Chen, B Yin… - ACM Transactions on …, 2024 - dl.acm.org
Adaptive transform coding is gaining more and more attention for better mining of image
content over fixed transforms such as discrete cosine transform (DCT). As a special case …
content over fixed transforms such as discrete cosine transform (DCT). As a special case …
Patch re-segmentation and packing for dynamic point cloud compression via back-and-forth structure
H Shi, F Li - IEEE Open Journal of Signal Processing, 2022 - ieeexplore.ieee.org
The dynamic point cloud is widely needed in 3D vision related applications such as virtual
reality and telepresence. Due to the huge amount of data, a key technology before the …
reality and telepresence. Due to the huge amount of data, a key technology before the …
Wavelet-like Transform with Subbands Fusion in Decoupled Structure for Deep Image Compression
Wavelet-like transform, based on convolutional neural network (CNN), is content-adaptive
and has made remarkable achievements in end-to-end image compression. However, the …
and has made remarkable achievements in end-to-end image compression. However, the …