Query：
学者姓名：陈建
Refining：
Year
Type
Indexed by
Source
Complex
Former Name
Co-
Language
Clean All
Abstract ：
As a new-generation video coding standard, Alliance for Open Media Video 1 (AV1) introduces flexible and diverse block partition types to improve coding efficiency, but also increases coding complexity. To address this issue, we propose a low-complexity AV1 intra prediction algorithm using Long-edge Sparse Sampling (LSS) and Chroma Migrating from Luma (CML) for efficiently encoding video sequences. First, we develop an LSS method by selecting key reference pixels based on block partition condition to reduce computational complexity. Second, we exploit a CML algorithm which combines the angle mode of the luma component and the spatial correlations of chroma components to derive more accurate linear model parameters between the luma and chroma components. Experimental results show that LSS avoids division operations, reducing 93% of addition operations. Combined with CML, our approach saves 4.97% time and enhances coding performance compared to standard AV1, particularly improving chroma component quality. © 2025
Keyword ：
Image coding Image coding NP-hard NP-hard Special effects Special effects Video streaming Video streaming
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | Huang, Wanwei , Xie, Xuan , Chen, Yu et al. Low-complexity AV1 intra prediction algorithm [J]. | Journal of Visual Communication and Image Representation , 2025 , 110 . |
| MLA | Huang, Wanwei et al. "Low-complexity AV1 intra prediction algorithm" . | Journal of Visual Communication and Image Representation 110 (2025) . |
| APA | Huang, Wanwei , Xie, Xuan , Chen, Yu , Wang, Baotu , Chen, Jian , Chen, Pingping . Low-complexity AV1 intra prediction algorithm . | Journal of Visual Communication and Image Representation , 2025 , 110 . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
三维建模和测量技术已经广泛应用于生物识别、医学辅助诊断、工业精密仪器加工与检测等领域.然而,现有的软件在重建精度和测量效果上难以满足复杂需求,且软件升级和功能优化受限.对此,使用去噪、精简、配准及补全等技术实现三维物体的点云建模,进而根据特征点信息精确测量目标物体的体积、表面积.实验数据显示,重建模型可视性好,物体体积和表面积的测量误差均在0.03％以内,验证了该测量算法的有效性.
Keyword ：
体积测量 体积测量 点云去噪 点云去噪 点云建模 点云建模
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | 朱宇耀 , 杜林莎 , 高峰 et al. 三维点云建模及测量算法研究 [J]. | 电视技术 , 2024 , 48 (10) : 67-71 . |
| MLA | 朱宇耀 et al. "三维点云建模及测量算法研究" . | 电视技术 48 . 10 (2024) : 67-71 . |
| APA | 朱宇耀 , 杜林莎 , 高峰 , 陈建 . 三维点云建模及测量算法研究 . | 电视技术 , 2024 , 48 (10) , 67-71 . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
针对AOMedia Video 1(AV1)编码时间较长的问题,基于不同纹理的视频内容与分区模式之间的联系,引入了虚拟子块的跨块梯度差来衡量图像纹理分布的差异,提出了一种快速块划分决策算法,以跳过非必要的分区模式.利用分区终止块大小与性能损失之间的联系,根据当前块大小自适应调整快速块划分的判断阈值,使得较小的编码块具有较宽松的跳过条件.与libaom相比,该算法在全帧内(All-Intra,AI)配置下平均可节省16.15%的编码时间,同时性能损失较小,有望被用于减少高分辨率视频的编码时间.
Keyword ：
AV1 AV1 分区决策 分区决策 梯度差异 梯度差异 视频编码 视频编码
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | 谢璇 , 黄婉溦 , 陈钰 et al. 结合视频内容的AV1快速块划分决策 [J]. | 无线电通信技术 , 2024 , 50 (5) : 1029-1036 . |
| MLA | 谢璇 et al. "结合视频内容的AV1快速块划分决策" . | 无线电通信技术 50 . 5 (2024) : 1029-1036 . |
| APA | 谢璇 , 黄婉溦 , 陈钰 , 王宝土 , 陈建 . 结合视频内容的AV1快速块划分决策 . | 无线电通信技术 , 2024 , 50 (5) , 1029-1036 . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
开放媒体联盟开发的第一代视频编码标准(Alliance for Open Media Video 1,AVI)作为新一代的开放式视频编码技术,以其高压缩效率和高质量视频输出等优势成为在线视频领域的主流编解码标准之一.旨在优化帧内预测编码技术以降低编码运行的计算复杂度,从而节约视频编码时间.为此,提出了长边采样(Long-side Sampling,LS)和长边稀疏采样(Long-side Sparse Sampling,LSS)的参考像素选择方法,根据块的划分方式规律地提取关键参考像素,以改进直流(Direct Current,DC)预测和亮度预测色度(Chroma from Luma,CfL)预测技术的性能.实验结果表明,LSS可以规避运算中的除法操作且减少大量加法计算量,在全I帧(All Intra,AI)和随机接入(Random Access,RA)配置下,相较原始算法平均编码时间减少11％和13％,同时节省0.03％和0.04％的Bjøntegaard Delta Bit Rate(BDBR).
Keyword ：
亮度预测色度 亮度预测色度 帧内预测 帧内预测 开放媒体联盟开发的第一代视频编码标准 开放媒体联盟开发的第一代视频编码标准 直流预测 直流预测 视频编码 视频编码
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | 黄婉溦 , 汪家华 , 刘昌沭 et al. 基于长边稀疏采样的AV1参考像素选择算法 [J]. | 无线电工程 , 2024 , 54 (10) : 2333-2338 . |
| MLA | 黄婉溦 et al. "基于长边稀疏采样的AV1参考像素选择算法" . | 无线电工程 54 . 10 (2024) : 2333-2338 . |
| APA | 黄婉溦 , 汪家华 , 刘昌沭 , 陈建 . 基于长边稀疏采样的AV1参考像素选择算法 . | 无线电工程 , 2024 , 54 (10) , 2333-2338 . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
Deblocking filtering plays a crucial role in high efficiency video coding (HEVC) by effectively enhancing the subjective quality of encoded images. It is one of the important means to improve overall video encoding performance. To address the high complexity associated with deblocking filtering technology in HEVC hardware encoders, in order to save resource consumption, reduced processing cycles, and improved filtering efficiency, a hardware algorithm and VLSI architecture for an adaptive deblocking filter in HEVC is proposed. First, based on the boundary rules of HEVC coding structure, a fast boundary judgment algorithm without recursive loop calculation is proposed to reduce the complexity of hardware implementation. Furthermore, based on the above boundary judgment results, a four-stage pipeline structure that can independently select the filter boundary for deblocking filtering is proposed to reduce the filter processing cycle. Finally, the luma and chroma components are filtered in parallel, utilizing a highly parallel and compatible shared memory architecture. This design not only enhances filtering efficiency but also minimizes memory resource consumption. Experimental results demonstrate that the hardware area of the designed deblock filtering structure is about 60% less than that of the existing structure under the TSMC90 nm process, and the maximum working frequency can reach 250 MHz, which can meet the real-time encoding of 8K@60fps ultra-high-definition video. © 2024 Institute of Computing Technology. All rights reserved.
Keyword ：
Efficiency Efficiency Encoding (symbols) Encoding (symbols) Image coding Image coding Image enhancement Image enhancement Integrated circuit design Integrated circuit design Memory architecture Memory architecture Pipeline processing systems Pipeline processing systems Signal encoding Signal encoding Structural design Structural design Video signal processing Video signal processing VLSI circuits VLSI circuits
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | Chen, Zhuomiao , Chen, Zhifeng , Chen, Jian et al. VLSI Design and Implementation of Adaptive Deblocking Filter for HEVC [J]. | Journal of Computer-Aided Design and Computer Graphics , 2024 , 36 (4) : 636-644 . |
| MLA | Chen, Zhuomiao et al. "VLSI Design and Implementation of Adaptive Deblocking Filter for HEVC" . | Journal of Computer-Aided Design and Computer Graphics 36 . 4 (2024) : 636-644 . |
| APA | Chen, Zhuomiao , Chen, Zhifeng , Chen, Jian , Wang, Jiahua . VLSI Design and Implementation of Adaptive Deblocking Filter for HEVC . | Journal of Computer-Aided Design and Computer Graphics , 2024 , 36 (4) , 636-644 . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
Learning-based point cloud compression has achieved great success in Rate-Distortion (RD) efficiency. Existing methods usually utilize Variational AutoEncoder (VAE) network, which might lead to poor detail reconstruction and high computational complexity. To address these issues, we propose a Scale-adaptive Asymmetric Sparse Variational AutoEncoder (SAS-VAE) in this work. First, we develop an Asymmetric Multiscale Sparse Convolution (AMSC), which exploits multi-resolution branches to aggregate multiscale features at encoder, and excludes symmetric feature fusion branches to control the model complexity at decoder. Second, we design a Scale Adaptive Feature Refinement Structure (SAFRS) to adaptively adjust the number of Feature Refinement Modules (FRMs), thereby improving RD performance with an acceptable computational overhead. Third, we implement our framework with AMSC and SAFRS, and train it with an RD loss based on Fine-grained Weighted Binary Cross-Entropy (FWBCE) function. Experimental results on 8iVFB, Owlii, and MVUV datasets show that our method outperforms several popular methods, with a 90.0% time reduction and a 51.8% BD-BR saving compared with V-PCC. The code will be available soon at https://github.com/fancj2017/SAS-VAE.
Keyword ：
asymmetric multiscale sparse convolution asymmetric multiscale sparse convolution Convolution Convolution Decoding Decoding Feature extraction Feature extraction Octrees Octrees Point cloud compression Point cloud compression Rate-distortion Rate-distortion scale adaptive feature refinement structure scale adaptive feature refinement structure Three-dimensional displays Three-dimensional displays variational autoencoder variational autoencoder
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | Chen, Jian , Zhu, Yingtao , Huang, Wei et al. Scale-Adaptive Asymmetric Sparse Variational AutoEncoder for Point Cloud Compression [J]. | IEEE TRANSACTIONS ON BROADCASTING , 2024 , 70 (3) : 884-894 . |
| MLA | Chen, Jian et al. "Scale-Adaptive Asymmetric Sparse Variational AutoEncoder for Point Cloud Compression" . | IEEE TRANSACTIONS ON BROADCASTING 70 . 3 (2024) : 884-894 . |
| APA | Chen, Jian , Zhu, Yingtao , Huang, Wei , Lan, Chengdong , Zhao, Tiesong . Scale-Adaptive Asymmetric Sparse Variational AutoEncoder for Point Cloud Compression . | IEEE TRANSACTIONS ON BROADCASTING , 2024 , 70 (3) , 884-894 . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
With the rapid development of image editing technology, tampering with images has become easier. Maliciously tampered images lead to serious security problems (e.g., when used as evidence). The current mainstream methods of image tampering are divided into three types which are copy-move, splicing and removal. Many image tampering detection methods can only detect one type of image tampering. Additionally, some methods learn features by suppressing image content, which can result in false positives when identifying tampered areas. In this paper, the authors propose a novel framework named the dual supervision neural network (DS-Net) to localize the tampered regions of images tampered by the three tampering methods mentioned above. First, to extract richer multiscale information, the authors add skip connections to the atrous spatial pyramid pooling (ASPP) module. Second, a channel attention mechanism is introduced to dynamically weigh the results generated by ASPP. Finally, the authors build additional supervised branches for high-level features to further enhance the extraction of these high-level features before fusing them with low-level features. The authors conduct experiments on various standard datasets. Through extensive experiments, the results show that the AUC scores reach 86.4%, 95.3% and 99.6% for CASIA, COVERAGE and NIST16 datasets, respectively, and the F1 scores are 56.0%, 73.4% and 82.7%, respectively. The results demonstrate that the authors' method can accurately locate tampered regions and achieve better performance on various datasets than other methods of the same type.
Keyword ：
image forensics image forensics image processing image processing
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | Dai, Chenwei , Su, Lichao , Wu, Bin et al. DS-Net: Dual supervision neural network for image manipulation localization [J]. | IET IMAGE PROCESSING , 2023 , 17 (12) : 3551-3563 . |
| MLA | Dai, Chenwei et al. "DS-Net: Dual supervision neural network for image manipulation localization" . | IET IMAGE PROCESSING 17 . 12 (2023) : 3551-3563 . |
| APA | Dai, Chenwei , Su, Lichao , Wu, Bin , Chen, Jian . DS-Net: Dual supervision neural network for image manipulation localization . | IET IMAGE PROCESSING , 2023 , 17 (12) , 3551-3563 . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
本发明提出一种基于激光雷达的点云实时采集压缩传输系统及方法，包括：实时采集激光雷达点云，对点云进行自适应编码和封装，实时传输，解封装和自适应解码，渲染可视化并保存本地。本系统具有时间复杂度低，实时性高的优点，根据带宽动态压缩后的数据在低带宽的情况下也可实现可靠低时延的传输，远程实时地观测并处理激光雷达采集的第一手3D点云数据。高带宽情况下该系统还可用于传输多路数据，符合车路协同、远程智能驾驶、机器人视觉等行业对远程采集传输点云数据并进行分析处理的低时延需求。
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | 陈建 , 黄炜 , 陈锋 et al. 基于激光雷达的点云实时采集压缩传输系统及方法 : CN202111074168.3[P]. | 2021-09-14 00:00:00 . |
| MLA | 陈建 et al. "基于激光雷达的点云实时采集压缩传输系统及方法" : CN202111074168.3. | 2021-09-14 00:00:00 . |
| APA | 陈建 , 黄炜 , 陈锋 , 郑明魁 , 黄昕 . 基于激光雷达的点云实时采集压缩传输系统及方法 : CN202111074168.3. | 2021-09-14 00:00:00 . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
去方块滤波(Deblocking Filtering,DBF)是高效视频编码(High Efficiency Video Coding,HEVC)的重要组成部分,能够有效地改善编码图像的主观质量,是提升视频整体编码性能的重要手段之一.但是去方块滤波技术复杂度较高.为解决该问题,设计一种HEVC去方块滤波器的硬件架构,在节省资源消耗的同时,减少处理周期并改善滤波效率.以8×4块为基本滤波单元,从输入像素到输出像素,采用四级流水线的形式进行处理,每处理一个基本滤波单元共花费5个周期.实验结果表明,所设计的去方块滤波器仅需5212个查找表和1291个寄存器的逻辑资源消耗,最高可达到215 MHz的工作频率,满足1080p@60fps的高清视频实时编码.
Keyword ：
去方块滤波(DBF) 去方块滤波(DBF) 环路滤波 环路滤波 高效视频编码(HEVC) 高效视频编码(HEVC)
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | 陈焯淼 , 陈志峰 , 陈建 et al. 基于FPGA的HEVC去方块滤波硬件设计 [J]. | 电视技术 , 2023 , 47 (1) : 48-51,69 . |
| MLA | 陈焯淼 et al. "基于FPGA的HEVC去方块滤波硬件设计" . | 电视技术 47 . 1 (2023) : 48-51,69 . |
| APA | 陈焯淼 , 陈志峰 , 陈建 , 汪家华 . 基于FPGA的HEVC去方块滤波硬件设计 . | 电视技术 , 2023 , 47 (1) , 48-51,69 . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
Recently, several in-loop filtering algorithms based on convolutional neural network (CNN) have been proposed to improve the efficiency of HEVC (High Efficiency Video Coding). Conventional CNN-based filters only apply a single model to the whole image, which cannot adapt well to all local features from the image. To solve this problem, an in-loop filtering algorithm based on a dynamic convolutional capsule network (DCC-net) is proposed, which embeds localized dynamic routing and dynamic segmentation algorithms into capsule network, and integrate them into the HEVC hybrid video coding framework as a new in-loop filter. The proposed method brings average 7.9% and 5.9% BD-BR reductions under all intra (AI) and random access (RA) configurations, respectively, as well as, 0.4 dB and 0.2 dB BD-PSNR gains, respectively. In addition, the proposed algorithm has an outstanding performance in terms of time efficiency.
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | Su, LiChao , Cao, Mengqing , Yu, Yue et al. Dynamic convolutional capsule network for In-loop filtering in HEVC video codec [J]. | IET IMAGE PROCESSING , 2022 , 17 (2) : 439-449 . |
| MLA | Su, LiChao et al. "Dynamic convolutional capsule network for In-loop filtering in HEVC video codec" . | IET IMAGE PROCESSING 17 . 2 (2022) : 439-449 . |
| APA | Su, LiChao , Cao, Mengqing , Yu, Yue , Chen, Jian , Yang, XiuZhi , Wu, Dapeng . Dynamic convolutional capsule network for In-loop filtering in HEVC video codec . | IET IMAGE PROCESSING , 2022 , 17 (2) , 439-449 . |
| Export to | NoteExpress RIS BibTex |
Version ：
Export
| Results： |
Selected to |
| Format： |
