266/VVC based on the improved DAG-SVM classifier model. Multimed Syst 1–14 Park S-H, Kang J (2020) Fast multi-type tree partitioning for versatile video coding using a lightweight neural network. IEEE Trans Multimed Messaoud S, Bradai A, Ahmed OB, Quang P, Atri M, Hossain MS (2020...
In addition, a dense residual convolutional neural network (DRN) for the VVC filtering method proposed was applied after DBF and before SAO and ALF [12]. The H.265/VVC fast-intra-CU coding technique is based on the improved DAG-SVM classifier to minimize CU partition complexity [21]. ...
2, for coding each frame xt with frame index t, our coding pipeline contains three core steps: fmotion, fT context, and fframe. At first, fmotion uses optical flow network to es- timate the motion vector (MV) vt, then vt is encoded and decoded as vˆt. Second, based on vˆt...
3. Method We first describe the architecture, block-based warping scheme, and training losses needed to train a 32-bit floating point model. We then describe the quantization procedure, and how we run entropy coding and inference on-device. 3.1. Network ...
The neural network-based estimation of local distortion sensitivity is presented in Section 3. Performance of the presented approach for neural network-based compensation for distortion sensitivity is evaluated and compared to other relevant approaches on the LIVE [25], the TID2013 [26] and the ...
2.2. Neural Image Compression Network Architecture Design. Neural image compres- sion has achieved some major breakthroughs in the past few years. Since the early attempts by Toderici et al. [35] to utilize convolutional LSTMs for image compression, conside...
This enhancement demonstrates the potential of self-attention mechanisms to revolutionize post-filtering techniques in video coding beyond the limitations of convolution-based methods. The experimental results show that the proposed network achieves an average BD-rate reduction of 10.40% for the Luma ...