CANF-VC++: Enhancing Conditional Augmented Normalizing Flows for Video Compression with Advanced Techniques

Video has become the predominant medium for information dissemination, driving the need for efficient video codecs. Recent advancements in learned video compression have shown promising results, surpassing traditional codecs in terms of coding efficiency. However, challenges remain in integrating fragmented techniques and incorporating new tools into existing codecs. In this paper, we comprehensively review the state-of-the-art CANF-VC codec and propose CANF-VC++, an enhanced version that addresses these challenges. We systematically explore architecture design, reference frame type, training procedure, and entropy coding efficiency, leading to substantial coding improvements. CANF-VC++ achieves significant Bj{\o}ntegaard-Delta rate savings on conventional datasets UVG, HEVC Class B and MCL-JCV, outperforming the baseline CANF-VC and even the H.266 reference software VTM. Our work demonstrates the potential of integrating advancements in video compression and serves as inspiration for future research in the field

OMRA: Online Motion Resolution Adaptation to Remedy Domain Shift in Learned Hierarchical B-frame Coding

Learned hierarchical B-frame coding aims to leverage bi-directional reference frames for better coding efficiency. However, the domain shift between training and test scenarios due to dataset limitations poses a challenge. This issue arises from training the codec with small groups of pictures (GOP) but testing it on large GOPs. Specifically, the motion estimation network, when trained on small GOPs, is unable to handle large motion at test time, incurring a negative impact on compression performance. To mitigate the domain shift, we present an online motion resolution adaptation (OMRA) method. It adapts the spatial resolution of video frames on a per-frame basis to suit the capability of the motion estimation network in a pre-trained B-frame codec. Our OMRA is an online, inference technique. It need not re-train the codec and is readily applicable to existing B-frame codecs that adopt hierarchical bi-directional prediction. Experimental results show that OMRA significantly enhances the compression performance of two state-of-the-art learned B-frame codecs on commonly used datasets.Comment: 7 pages, submitted to IEEE ICIP 202

Transformer-based Image Compression with Variable Image Quality Objectives

This paper presents a Transformer-based image compression system that allows for a variable image quality objective according to the user's preference. Optimizing a learned codec for different quality objectives leads to reconstructed images with varying visual characteristics. Our method provides the user with the flexibility to choose a trade-off between two image quality objectives using a single, shared model. Motivated by the success of prompt-tuning techniques, we introduce prompt tokens to condition our Transformer-based autoencoder. These prompt tokens are generated adaptively based on the user's preference and input image through learning a prompt generation network. Extensive experiments on commonly used quality metrics demonstrate the effectiveness of our method in adapting the encoding and/or decoding processes to a variable quality objective. While offering the additional flexibility, our proposed method performs comparably to the single-objective methods in terms of rate-distortion performance

Different Dietary Proportions of Fish Oil Regulate Inflammatory Factors but Do Not Change Intestinal Tight Junction ZO-1 Expression in Ethanol-Fed Rats

Sixty male Wistar rats were fed a control or an ethanol-containing diet in groups C or E. The fat compositions were adjusted with 25% or 57% fish oil substituted for olive oil in groups CF25, CF57, EF25, and EF57. Hepatic thiobarbituric acid-reactive substance (TBARS) levels, cytochrome P450 2E1 protein expression, and tumor necrosis factor- (TNF-) α, interleukin- (IL-) 1β, IL-6, and IL-10 levels, as well as intracellular adhesion molecule (ICAM)-1 levels were significantly elevated, whereas plasma adiponectin level was significantly reduced in group E (p<0.05). Hepatic histopathological scores of fatty change and inflammation, in group E were significantly higher than those of group C (p<0.05). Hepatic TBARS, plasma ICAM-1, and hepatic TNF-α, IL-1β, and IL-10 levels were significantly lower, and plasma adiponectin levels were significantly higher in groups EF25 and EF57 than those in group E (p<0.05). The immunoreactive area of the intestinal tight junction protein, ZO-1, showed no change between groups C and E. Only group CF57 displayed a significantly higher ZO-1 immunoreactive area compared to group C (p=0.0415). 25% or 57% fish oil substituted for dietary olive oil could prevent ethanol-induced liver damage in rats, but the mechanism might not be related to intestinal tight junction ZO-1 expression