Marek Domański

Sławomir Maćkowiak, Marek Domański, Sławomir Różek et al.

The paper deals with Video Coding for Machines that is a new paradigm in video coding related to consumption of decoded video by humans and machines. For such tasks, joint transmission of compressed video and features is considered. In this paper, we focus our considerations of features on SIFT keypoints. They can be extracted from the decoded video with losses in number of keypoints and their parameters as compared to the SIFT keypoints extracted from the original video. Such losses are studied for HEVC and VVC as functions of the quantization parameter and the bitrate. In the paper, we propose to transmit the residual feature data together with the compressed video. Therefore, even for strongly compressed video, the transmission of whole all SIFT keypoint information is avoided.

Yung-Han Ho, Chih-Chun Chan, Wen-Hsiao Peng et al.

This paper introduces an end-to-end learned image compression system, termed ANFIC, based on Augmented Normalizing Flows (ANF). ANF is a new type of flow model, which stacks multiple variational autoencoders (VAE) for greater model expressiveness. The VAE-based image compression has gone mainstream, showing promising compression performance. Our work presents the first attempt to leverage VAE-based compression in a flow-based framework. ANFIC advances further compression efficiency by stacking and extending hierarchically multiple VAE's. The invertibility of ANF, together with our training strategies, enables ANFIC to support a wide range of quality levels without changing the encoding and decoding networks. Extensive experimental results show that in terms of PSNR-RGB, ANFIC performs comparably to or better than the state-of-the-art learned image compression. Moreover, it performs close to VVC intra coding, from low-rate compression up to nearly-lossless compression. In particular, ANFIC achieves the state-of-the-art performance, when extended with conditional convolution for variable rate compression with a single model.

Jarosław Samelak, Marek Domański

The paper presents a new approach to multiview video coding using Screen Content Coding. It is assumed that for a time instant the frames corresponding to all views are packed into a single frame, i.e. the frame-compatible approach to multiview coding is applied. For such coding scenario, the paper demonstrates that Screen Content Coding can be efficiently used for multiview video coding. Two approaches are considered: the first using standard HEVC Screen Content Coding, and the second using Advanced Screen Content Coding. The latter is the original proposal of the authors that exploits quarter-pel motion vectors and other nonstandard extensions of HEVC Screen Content Coding. The experimental results demonstrate that multiview video coding even using standard HEVC Screen Content Coding is much more efficient than simulcast HEVC coding. The proposed Advanced Screen Content Coding provides virtually the same coding efficiency as MV-HEVC, which is the state-of-the-art multiview video compression technique. The authors suggest that Advanced Screen Content Coding can be efficiently used within the new Versatile Video Coding (VVC) technology. Nevertheless a reference multiview extension of VVC does not exist yet, therefore, for VVC-based coding, the experimental comparisons are left for future work.

Dawid Mieloch, Olgierd Stankiewicz, Marek Domański

The paper presents a new method of depth estimation dedicated for free-viewpoint television (FTV). The estimation is performed for segments and thus their size can be used to control a trade-off between the quality of depth maps and the processing time of their estimation. The proposed algorithm can take as its input multiple arbitrarily positioned views which are simultaneously used to produce multiple inter view consistent output depth maps. The presented depth estimation method uses novel parallelization and temporal consistency enhancement methods that significantly reduce the processing time of depth estimation. An experimental assessment of the proposals has been performed, based on the analysis of virtual view quality in FTV. The results show that the proposed method provides an improvement of the depth map quality over the state of-the-art method, simultaneously reducing the complexity of depth estimation. The consistency of depth maps, which is crucial for the quality of the synthesized video and thus the quality of experience of navigating through a 3D scene, is also vastly improved.

Krzysztof Wegner, Tomasz Grajek, Jakub Stankowski et al.

HEVC (MPEG-H Part 2 and H.265) is a new coding technology which is expected to be deployed on the market along with new video services in the near future. HEVC is a successor of currently widely used AVC (MPEG-4 Part 10 and H.264). In this paper, the quality coding gains obtained for the Cascaded Pixel Domain Transcoder of AVC-coded material to HEVC standard are reported. Extensive experiments showed that transcoding with bitrate reduction allows the achievement of better rate-distortion performance than by compressing an original video sequence with the use of AVC at the same (reduced) bitrate.