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2024 conference on Visual communications and image processing

作者： Yang, Ruolin Li, Da Zhang, Honggang Song, Yi-Zhe Beijing Univ Posts & Telecommun Sch Artificial Intelligence PRIS Beijing Peoples R China Univ Surrey SketchX CVSSP Guildford Surrey England

ISBN: (纸本)9798331529543;9798331529550

Sketching is a uniquely human tool for expressing ideas and creativity. The animation of sketches infuses life into these static drawings, opening a new dimension for designers. Animating sketches is a time-consuming process that demands professional skills and extensive experience, often proving daunting for amateurs. In this paper, we propose a novel sketch animation model SketchAnimator, which enables adding creative motion to a given sketch, like "a jumping car". Namely, given an input sketch and a reference video, we divide the sketch animation into three stages: Appearance Learning, Motion Learning and video Prior Distillation. In stages 1 and 2, we utilize LoRA to integrate sketch appearance information and motion dynamics from the reference video into the pre-trained T2V model. In the third stage, we utilize Score Distillation Sampling (SDS) to update the parameters of the Bezier curves in each sketch frame according to the acquired motion information. Consequently, our model produces a sketch video that not only retains the original appearance of the sketch but also mirrors the dynamic movements of the reference video. We compare our method with alternative approaches and demonstrate that it generates the desired sketch video under the challenge of one-shot motion customization.

关键词： Sketch animation diffusion process generative model video generation motion extraction

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Frame Level Content Adaptive λ for Neural video Compression

Frame Level Content Adaptive λ for Neural Video Compression

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2024 conference on Visual communications and image processing

作者： Zuo, Zhirui Liao, Junqi Song, Xiaomin Liu, Zheng Zheng, Huiming Liu, Dong Univ Sci & Technol China Hefei Peoples R China Sichuan Xinshi Chuangwei Ultra HD Technol Co Ltd Chengdu Peoples R China

ISBN: (纸本)9798331529543;9798331529550

Neural video compression (NVC) methods have made significant advances in recent years. In most NVC methods, all frames share the same Rate-Distortion trade-off parameter lambda, which might be sub-optimal. Recently, inspired by traditional video codecs' hierarchical quality structure, DCVC-DC proposed allocating periodic weights to lambda to equip NVC with the hierarchical quality structure. However, the inspiration from traditional video codecs is designed to complement their complex reference structure. Compared to traditional video codecs, NVC methods' reference structure is much simpler and may not require large fluctuations in their hierarchical quality structure. Moreover, DCVC-DC's fixed hierarchical quality structure ignored the influence of video content. We conduct an elaborate study on the hierarchical quality structure in DCVC-DC, shedding light on the potential for improving compression performance by proposing a content adaptive lambda to achieve a more reasonable hierarchical quality structure based on the fixed hierarchical weights. Experimental results demonstrate that the proposed method achieves a better rate-distortion performance than allocating the fixed weights to the fixed lambda. On DCVC-DC and DCVC-SDD, we achieved 4.9% and 8.8% bdrate reduction with our method.

关键词： Content Adaptive lambda Hierarchical Quality Structure Neural video Compression

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Dynamic Volumetric video Coding with Tensor Decomposition

Dynamic Volumetric Video Coding with Tensor Decomposition

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2024 conference on Visual communications and image processing

作者： Shin, Ju-Yeon Kim, Yeoneui Kang, Je-Won Bang, Gun Ewha Womans Univ Dept Elect & Elect Engn Seoul South Korea Ewha Womans Univ Grad Program Smart Factory Seoul South Korea Elect & Telecommun Res Inst Daejeon South Korea

ISBN: (纸本)9798331529543;9798331529550

Recently, volumetric video coding based on neural radiance fields has gained significant attention for storing and transmitting three-dimensional (3D) scenes captured from multiview video. Because the neural networks are trained to produce novel view synthesis of surrounding 3D scenes, compressing the model and then rendering the colors and geometry through the decompressed model can be utilized as a 3D video coding system. However, although this approach provides superior performance compared to conventional 3D video coding standards using depth video, challenges remain in reducing overall model sizes to improve coding efficiency. In this paper, we propose a novel dynamic volumetric video coding technique that employs a Group of Volume (GoV) to divide multi-view video sequences into smaller chunks, addressing complex temporal dynamics. Our method uses volumetric video features represented with 3D spatial and temporal tensor matrices and vectors and encodes them with the GoVs. The tensors are compressed by existing 2D video codec, allowing for fast rendering and easing deployment. Experimental results validate that our method not only reduces memory footprint but also maintains high-quality rendering as compared to state-of-the-art studies.

关键词： Volumetric video Coding Neural Radiance Fields Voxel-grid Representation and 3D video Coding Standards

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Improving Reconstruction Fidelity in Generative Face video Coding using High-Frequency Shuttling

Improving Reconstruction Fidelity in Generative Face Video C...

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2024 conference on Visual communications and image processing

作者： Konuko, Goluck Valenzise, Giuseppe Trioux, Anthony Univ Paris Saclay Lab Signaux & Syst Cent Supelec CNRS Gif Sur Yvette France Xidian Univ Sch Telecommun Engn Xian Peoples R China

ISBN: (纸本)9798331529543;9798331529550

Generative face video coding (GFVC) schemes applied to talking head videos have recently demonstrated significant coding gains compared to traditional coding frameworks, particularly at ultra-low bitrates. Despite advancements in the field, these methods still face challenges in handling large pose and facial expression changes, as well as (dis-)occlusions. Recently, a hybrid approach (HDAC+) that combines a low-quality video coded with a conventional codec and animation-based coding has been proposed for standardization and shown to partially address these issues. Although HDAC+ shows promising results, it still struggles with generating accurate images. In this paper, we propose HDAC-HF, an improvement to the reconstruction process in HDAC+. Based on empirical observations that some pose and expression details are lost during animation, we introduce a high-frequency (HF) shuttling mechanism to enhance reconstruction fidelity at the decoder side, inspired by recent advancements in video super-resolution. By enhancing the flow of high-frequency details in the feature domain, we improve the reconstruction of facial expressions and poses. Qualitative and quantitative experiments confirm that the proposed method improves reconstruction without any additional bitstream or signaling cost compared to the baseline HDAC+ codec.

关键词： video Compression Generative Face video Coding Frequency Shuttling video Conferencing

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Compensation of Communication Latency in Remote Monitoring Systems by video Prediction

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IEICE TRANSACTIONS ON communications 2024年第12期E107B卷 945-954页

作者： Sato, Toshio Katsuyama, Yutaka Qi, Xin Wen, Zheng Tamesue, Kazuhiko Kameyama, Wataru Nakamura, Yuichi Katto, Jiro Sato, Takuro Waseda Univ Fac Sci & Engn Tokyo 1690072 Japan Waseda Univ Sch Int Liberal Studies Tokyo 1690051 Japan Kyoto Univ Grad Sch Biostudies Kyoto 6068501 Japan

Remote video monitoring over networks inevitably introduces a certain degree of communication latency. Although numerous studies have been conducted to reduce latency in network systems, achieving "zero-latency" is fundamentally impossible for video monitoring. To address this issue, we investigate a practical method to compensate for latency in video monitoring using video prediction techniques. We apply the lightweight PredNet to predict future frames, and their image qualities are evaluated through quantitative image quality metrics and subjective assessment. The evaluation results suggest that for simple movements the robot arm, the prediction time to generate future frames can tolerate up to 333 ms. The video prediction method is integrated into a remote monitoring system, and its processing time is also evaluated. We define the object-to-display latency for video monitoring and explore the potential for realizing a zero-latency remote video monitoring system. The evaluation, involving simultaneous capture of the robot arm's movement and the display of the remote monitoring system, confirms the feasibility of compensating for the object-to-display latency of several hundred milliseconds by using video prediction. Experimental results demonstrate that our approach can function as a new compensation method for communication latency.

关键词： video prediction zero-latency remote video monitoring Pred- Net image quality object-to-display latency

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Benchmarking Conventional and Learned video Codecs with a Low-Delay Configuration

Benchmarking Conventional and Learned Video Codecs with a Lo...

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2024 conference on Visual communications and image processing

作者： Teng, Siyue Jiang, Yuxuan Gao, Ge Zhang, Fan Davis, Thomas Liu, Zoe Bull, David Univ Bristol Visual Informat Lab Bristol BS1 5DD Avon England Visionular Inc Los Altos CA 94022 USA

ISBN: (纸本)9798331529543;9798331529550

Recent advances in video compression have seen significant coding performance improvements with the development of new standards and learning-based video codecs. However, most of these works focus on application scenarios that allow a certain amount of system delay (e.g., Random Access mode in MPEG codecs), which is not always acceptable for live delivery. This paper conducts a comparative study of state-of-the-art conventional and learned video coding methods based on a low delay configuration. Specifically, this study includes two MPEG standard codecs (H.266/VVC VTM and JVET ECM), two AOM codecs (AV1 libaom and AVM), and two recent neural video coding models (DCVC-DC and DCVC-FM). To allow a fair and meaningful comparison, the evaluation was performed on test sequences defined in the AOM and MPEG common test conditions in the YCbCr 4:2:0 color space. The evaluation results show that the JVET ECM codecs offer the best overall coding performance among all codecs tested, with a 16.1% (based on PSNR) average BD-rate saving over AOM AVM, and 11.0% over DCVC-FM. We also observed inconsistent performance with the learned video codecs, DCVC-DC and DCVC-FM, for test content with large background motions.

关键词： video compression low delay codec comparison learned video compression

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Advanced Learning-Based Inter Prediction for Future video Coding

Advanced Learning-Based Inter Prediction for Future Video Co...

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2024 conference on Visual communications and image processing

作者： Zhao, Yanchen Duan, Wenhong Jia, Chuanmin Wang, Shanshe Ma, Siwei Peking Univ Sch Comp Sci Beijing Peoples R China Peking Univ Wangxuan Inst Comp Technol Beijing Peoples R China

ISBN: (纸本)9798331529543;9798331529550

In the fourth generation Audio video coding Standard (AVS4), the Inter Prediction Filter (INTERPF) reduces discontinuities between prediction and adjacent reconstructed pixels in inter prediction. The paper proposes a low complexity learning-based inter prediction (LLIP) method to replace the traditional INTERPF. LLIP enhances the filtering process by leveraging a lightweight neural network model, where parameters can be exported for efficient inference. Specifically, we extract pixels and coordinates utilized by the traditional INTERPF to form the training dataset. Subsequently, we export the weights and biases of the trained neural network model and implement the inference process without any third-party dependency, enabling seamless integration into video codec without relying on Libtorch, thus achieving faster inference speed. Ultimately, we replace the traditional handcraft filtering parameters in INTERPF with the learned optimal filtering parameters. This practical solution makes the combination of deep learning encoding tools with traditional video encoding schemes more efficient. Experimental results show that our approach achieves 0.01%, 0.31%, and 0.25% coding gain for the Y, U, and V components under the random access (RA) configuration on average.

关键词： video coding inter prediction learning-based complexity reduction audio video coding standard

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Content-Adaptive Rate-Quality Curve Prediction Model in Media processing System

Content-Adaptive Rate-Quality Curve Prediction Model in Medi...

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2024 conference on Visual communications and image processing

作者： Yin, Shibo Zhang, Zhiyu Ning, Peirong Chen, Qiubo Chen, Jing Zhou, Quan Lu, Guo Song, Li Xiaohongshu Inc Shanghai Peoples R China Shanghai Jiao Tong Univ Shanghai Peoples R China

ISBN: (纸本)9798331529543;9798331529550

In streaming media services, video transcoding is a common practice to alleviate bandwidth demands. Unfortunately, traditional methods employing a uniform rate factor (RF) across all videos often result in significant inefficiencies. Content-adaptive encoding (CAE) techniques address this by dynamically adjusting encoding parameters based on video content characteristics. However, existing CAE methods are often tightly coupled with specific encoding strategies, leading to inflexibility. In this paper, we propose a model that predicts both RF-quality and RF-bitrate curves, which can be utilized to derive a comprehensive bitrate-quality curve. This approach facilitates flexible adjustments to the encoding strategy without necessitating model retraining. The model leverages codec features, content features, and anchor features to predict the bitrate-quality curve accurately. Additionally, we introduce an anchor suspension method to enhance prediction accuracy. Experiments confirm that the actual quality metric (VMAF) of the compressed video stays within +/- 1 of the target, achieving an accuracy of 99.14%. By incorporating our quality improvement strategy with the rate-quality curve prediction model, we conducted online A/B tests, obtaining both +0.107% improvements in video views and video completions and +0.064% app duration time. Our model has been deployed on the Xiaohongshu App.

关键词： Prediction models

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Decoding Complexity-Rate-Quality Pareto-Front for Adaptive VVC Streaming

Decoding Complexity-Rate-Quality Pareto-Front for Adaptive V...

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2024 conference on Visual communications and image processing

作者： Katsenou, Angeliki Menon, Vignesh V. Wieckowski, Adam Bross, Benjamin Marpe, Detlev Univ Bristol Bristol Digital Futures Inst Bristol Avon England Fraunhofer HHI Video Commun & Applicat Dept Berlin Germany

ISBN: (纸本)9798331529543;9798331529550

Pareto-front optimization is crucial for addressing the multi-objective challenges in video streaming, enabling the identification of optimal trade-offs between conflicting goals such as bitrate, video quality, and decoding complexity. This paper explores the construction of efficient bitrate ladders for adaptive Versatile video Coding (VVC) streaming, focusing on optimizing these trade-offs. We investigate various ladder construction methods based on Pareto-front optimization, including exhaustive Rate-Quality and fixed ladder approaches. We propose a joint decoding time-rate-quality Pareto-front, providing a comprehensive framework to balance bitrate, decoding time, and video quality in video streaming. This allows streaming services to tailor their encoding strategies to meet specific requirements, prioritizing low decoding latency, bandwidth efficiency, or a balanced approach, thus enhancing the overall user experience. The experimental results confirm and demonstrate these opportunities for navigating the decoding time-rate-quality space to support various use cases. For example, when prioritizing low decoding latency, the proposed method achieves a decoding time reduction of 14.86% while providing Bjontegaard delta rate savings of 4.65% and 0.32 dB improvement in the eXtended Peak Signal-to-Noise Ratio (XPSNR)-Rate domain over the traditional fixed ladder solution.

关键词： Pareto-front optimization Adaptive streaming Versatile video Coding (VVC) Bitrate ladder XPSNR

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Adaptive Block-Level Quality Parameter Adjustment Towards Low video Bit-Rate Fluctuation

Adaptive Block-Level Quality Parameter Adjustment Towards Lo...

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2024 conference on Visual communications and image processing

作者： Feng, Longtao Yin, Qian Ren, Huiwen Wang, Zhao Ma, Siwei He, Yuwen Peking Univ Natl Engn Res Ctr Visual Technol Sch Comp Sci Beijing Peoples R China Peking Univ Adv Inst Informat Technol Beijing Peoples R China Bytedance Inc San Diego CA USA

ISBN: (纸本)9798331529543;9798331529550

Existing quantization parameter (QP) adjustment methods in video coding often focus solely on coding efficiency and ignore the impact of bit-rate fluctuations on video transmission and bandwidth waste. This is mainly because intra pictures, in a hierarchical coding structure, are allocated smaller QP and thus consume more bits. To address this issue, we propose an adaptive block-level QP adjustment method. Specifically, intra picture importance (IPI) is first introduced to evaluate the adjustability of intra picture QP. For intra pictures whose QP can be adjusted, we further propose block importance (BI) to determine their optimal block-level QP adjustment. Experimental results show that our proposed method reduce the bit-rate fluctuations while basically maintaining the coding performance. Notably, significant improvements can be observed in high-resolution videos, with a reduction of approximately 11% in bit-rate fluctuations.

关键词： video Coding Quantization Parameter Bit-Rate Fluctuation

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