Telecommunications Science ›› 2021, Vol. 37 ›› Issue (4): 73-81.doi: 10.11959/j.issn.1000-0801.2021062
• Research and Development • Previous Articles Next Articles
Shuang PENG1, Xiaodong WANG1, Zongju PENG1,2, Fen CHEN2
Revised:
2021-04-10
Online:
2021-04-20
Published:
2021-04-01
Supported by:
CLC Number:
Shuang PENG, Xiaodong WANG, Zongju PENG, Fen CHEN. Fast QTMT partition decision based on deep learning[J]. Telecommunications Science, 2021, 37(4): 73-81.
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类 | 序列 | 本文所提算法(ω=0.85) | Lei等[ | Fu等[ | 本文所提算法(ω=1) | Yang等[ | 本文所提算法(ω=∞) | |||||||||||
BD-BR | ATR | BD-BR | ATR | BD-BR | ATR | BD-BR | ATR | BD-BR | ATR | BD-BR | ATR | |||||||
A1 | Tango2 | 1.19% | 40.19% | 0.97% | 46.80% | 1.72% | 54.00% | 1.52% | 44.57% | 0.99% | 50.98% | 2.96% | 57.00% | |||||
FoodMarket4 | 0.73% | 26.41% | 0.59% | 45.90% | 1.18% | 53.00% | 0.84% | 27.29% | 0.62% | 53.53% | 2.62% | 44.55% | ||||||
Campfire* | 1.29% | 44.37% | 0.81% | 42.10% | 1.04% | 46.00% | 1.70% | 50.92% | 0.95% | 49.67% | 2.84% | 59.00% | ||||||
A2 | Catrobot1 | 1.37% | 41.47% | 1.19% | 41.60% | 1.51% | 43.00% | 1.85% | 48.21% | 1.05% | 44.75% | 3.08% | 58.43% | |||||
DaylightRoad2 | 1.33% | 50.09% | 1.17% | 45.40% | 1.53% | 49.00% | 1.84% | 55.84% | 0.43% | 60.83% | 2.81% | 66.12% | ||||||
ParkRunning3* | 1.34% | 32.57% | 0.52% | 31.50% | 0.54% | 51.00% | 1.60% | 39.18% | 0.82% | 53.67% | 2.37% | 52.95% | ||||||
B | MarketPlace | 1.40% | 45.40% | 0.88% | 45.10% | 0.76% | 52.00% | 1.61% | 51.18% | — | — | 2.99% | 64.30% | |||||
RitualDance | 1.60% | 44.06% | 1.10% | 45.60% | 1.14% | 45.00% | 2.18% | 51.29% | — | — | 3.74% | 59.89% | ||||||
Cactus* | 1.32% | 51.16% | 1.02% | 41.90% | 0.96% | 44.00% | 1.60% | 56.53% | 1.95% | 56.66% | 2.75% | 65.70% | ||||||
C | BasketballDrive | 1.26% | 51.75% | 0.82% | 47.20% | 0.95% | 49.00% | 1.38% | 54.86% | 2.25% | 64.01% | 2.75% | 64.87% | |||||
BQTerrace | 1.51% | 54.52% | 1.47% | 45.50% | 0.79% | 48.00% | 1.96% | 59.63% | 2.07% | 56.07% | 2.71% | 66.99% | ||||||
BasketballDrill | 1.54% | 48.93% | 0.82% | 45.70% | 1.89% | 46.00% | 1.84% | 52.83% | 2.01% | 48.19% | 3.56% | 63.80% | ||||||
BQMall* | 0.67% | 57.70% | 0.89% | 46.90% | 0.87% | 39.00% | 0.85% | 61.26% | 2.15% | 55.23% | 1.59% | 67.43% | ||||||
D | PartyScene | 0.54% | 56.58% | 0.63% | 44.20% | 0.46% | 42.00% | 0.63% | 58.53% | 0.60% | 45.73% | 1.11% | 65.08% | |||||
RaceHorsesC | 0.83% | 54.58% | 2.03% | 56.20% | 0.71% | 42.00% | 1.05% | 59.05% | 1.16% | 48.39% | 1.77% | 65.88% | ||||||
BasketballPass* | 0.71% | 53.90% | 0.99% | 44.40% | 0.70% | 43.00% | 0.79% | 54.25% | 2.33% | 45.85% | 1.65% | 61.37% | ||||||
E | Bqsquare | 0.61% | 56.22% | 0.89% | 43.10% | 0.47% | 44.00% | 0.75% | 58.24% | 0.81% | 46.06% | 1.32% | 64.18% | |||||
BlowingBubbles | 0.70% | 50.63% | 0.91% | 47.10% | 0.56% | 37.00% | 0.82% | 53.57% | 0.77% | 41.56% | 1.46% | 60.41% | ||||||
RaceHorses | 0.75% | 48.76% | 1.07% | 42.00% | 0.75% | 39.00% | 1.01% | 52.44% | 0.86% | 43.17% | 1.76% | 59.62% | ||||||
FourPeople | 0.84% | 52.84% | 1.42% | 51.10% | 1.37% | 41.00% | 1.00% | 57.86% | 2.75% | 57.64% | 2.08% | 67.83% | ||||||
Johnny* | 0.92% | 53.74% | 1.35% | 46.20% | 1.33% | 39.00% | 1.54% | 60.83% | 3.29% | 58.98% | 2.47% | 65.32% | ||||||
KristenAndSara | 0.74% | 53.74% | 1.20% | 46.30% | 1.24% | 40.00% | 0.99% | 56.04% | 2.51% | 59.19% | 1.94% | 63.43% | ||||||
[1] | JCT-VC. High efficiency video coding (HEVC) text specification draft 10:JCTVC-L1003[S]. 2013. |
[2] | JVET. Meeting report of the 10th JVET meeting:JVET-J1000[S]. 2018. |
[3] | JVET. Algorithm description for versatile video coding and test model 2:JEVT-K1002[S]. 2018. |
[4] | 周芸, 胡潇, 郭晓强 . H.266/VVC视频编码图像划分技术研究[J]. 广播与电视技术, 2019,46(11): 40-44. |
ZHOU Y , HU X , GUO X Q . [J]. Research on image partition technolo-gy in H.266/VVC, 2019,46(11): 40-44. | |
[5] | JVET. AHG report:test model software development (AHG3):JVET-J0003[S]. 2018. |
[6] | PAKDAMAN F , ADELIMANESH M A , GABBOUJ M ,et al. Complexity analysis of next-generation VVC encoding and decod-ing[EB]. 2020.Arxiv:2005.10801. |
[7] | 姚英彪, 李晓娟 . 基于图像空间相关性与纹理的HEVC块划分快速算法[J]. 电信科学, 2015,31(1): 38-46. |
YAO Y B , LI X J . Fast block partitioning algorithm for HEVC based on spatial correlation and image texture[J]. Telecommunica-tions Science, 2015,31(1): 38-46. | |
[8] | KUO Y , CHEN P , LIN H . A spatiotemporal content-based CU size decision algorithm for HEVC[J]. IEEE Transactions on Broadcast-ing, 2020,1(66): 100-112. |
[9] | JAMALI M , COULOMBE S . Fast HEVC intra mode decision base on RDO cost prediction[J]. IEEE Transactions on Broadcasting, 2019,1(65): 109-122. |
[10] | HUANG B , CHEN Z , CAI Q ,et al. Rate-distortion-complexity optimized coding mode decision for HEVC[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2020,3(30): 795-809. |
[11] | LEI M , LUO F , ZHANG X ,et al. Look-ahead prediction based coding unit size pruning for VVC intra coding[C]// Proceedings of IEEE International Conference on Image Processing. Piscataway:IEEE Press, 2019: 4120-4124. |
[12] | CHEN J , SUN H , KATTO J ,et al. Fast QTMT partition decision algorithm in VVC intra coding based on variance and gradient[C]// Proceedings of IEEE Visual Communications and Image Processing. Piscataway:IEEE Press, 2019: 1-4. |
[13] | FAN Y , CHEN J , SUN H ,et al. A fast QTMT partition decision strategy for VVC intra prediction[J]. IEEE Access, 2020(8): 107900-107911. |
[14] | PARK S , KANG J . Context-based ternary tree decision method in versatile video coding for fast intra coding[J]. IEEE Access, 2019(7): 172597-172605. |
[15] | PARK S , KANG J . Fast affine motion estimation for versatile video coding (VVC) encoding[J]. IEEE Access, 2019(7): 158075-158084. |
[16] | LIU X , LI Y , LIU D ,et al. An adaptive CU size decision algorithm for HEVC intra prediction based on complexity classification using machine learning[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2019,1(29): 144-155. |
[17] | CHEN Z , SHI J , LI W . Learned fast HEVC intra coding[J]. IEEE Transactions on Image Processing, 2020(29): 5431-5446. |
[18] | KATAYAMA T , KURODA K , SHI W ,et al. Low-complexity intra coding algorithm based on convolutional neural network for HEVC[C]// Proceedings of International Conference on Information and Computer Technologies. Piscataway:IEEE Press, 2018: 115-118. |
[19] | KIM K , RO W W . Fast CU depth decision for HEVC using neural networks[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2019,5(29): 1462-1473. |
[20] | XU M , LI T Y , WANG Z ,et al. Reducing complexity of HEVC:a deep learning approach[J]. IEEE Transactions on Image Processing, 2018,10(27): 5044-5059. |
[21] | TANG G , JING M , ZENG X ,et al. Adaptive CU split decision with pooling-variable CNN for VVC intra encoding[C]// Proceedings of IEEE Visual Communications and Image Processing. Piscataway:IEEE Press, 2019: 1-4. |
[22] | YANG H , SHEN L , DONG X ,et al. Low-complexity CTU partition structure decision and fast intra mode decision for versatile video coding[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2020,6(30): 1668-1682. |
[23] | FU T , ZHANG H , MU F.Fast CU partitioning algorithm for H . 266/VVC intra-frame coding[C]// Proceedings of IEEE International Conference on Multimedia and Expo. Piscataway:IEEE Press, 2019: 55-60. |
[24] | AMESTOY T , MERCAT A , HAMIDOUCHE W ,et al. Tunable VVC frame partitioning based on lightweight machine learning[J]. IEEE Transactions on Image Processing, 2020(29): 1313-1328. |
[25] | 贾川民, 赵政辉, 王苫社 ,等. 基于神经网络的图像视频编码[J]. 电信科学, 2019,35(5): 32-42. |
JIA C M , ZHAO Z H , WANG S S ,et al. Neural network based im-age and video coding technologies[J]. Telecommunications Science, 2019,35(5): 32-42. | |
[26] | WIECKOWSKI A , MA J , SCHWARZ H ,et al. Fast partitioning decision strategies for the upcoming versatile video coding (VVC) standard[C]// Proceedings of IEEE International Conference on Image Processing. Piscataway:IEEE Press, 2019: 4130-4134. |
[27] | HU J , SHEN L , SUN G . Squeeze-and-excitation networks[C]// Proceedings of IEEE/CVF Conference on Computer Vision and Pattern Recognition. Piscataway:IEEE Press, 2018: 7132-7141. |
[28] | CHEN Y P , DAI X Y , LIU M C . Dynamic convolution:attention over convolution kernels[C]// Proceedings of IEEE/CVF Conference on Computer Vision and Pattern RecognitionA. Piscataway:IEEE Press, 2020: 11030-11039. |
[29] | JVET. Algorithm description for versatile video coding and test model 7:JEVT-P2002[S]. 2019. |
[30] | JVET. JVET common test conditions and software reference configurations:JEVT-K1010[S]. 2018. |
[31] | VCEG. Calculation of average PSNR differences between RD curves:VCEG-M33[S]. 2001. |
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