FCA-Net: Accelerating stereo image compression through cascade alignment of side information
Multi-view signal compression, particularly Stereo Image Compression (SIC), plays a pivotal role in applications such as car-mounted cameras and 3D-related scenarios. Despite the Distributed Source Coding (DSC) theory suggesting efficient compression through independent encoding and joint decoding,...
Saved in:
| Published in: | Pattern recognition Vol. 168; p. 111799 |
|---|---|
| Main Authors: | , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier Ltd
01.12.2025
|
| Subjects: | |
| ISSN: | 0031-3203 |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Abstract | Multi-view signal compression, particularly Stereo Image Compression (SIC), plays a pivotal role in applications such as car-mounted cameras and 3D-related scenarios. Despite the Distributed Source Coding (DSC) theory suggesting efficient compression through independent encoding and joint decoding, recent approaches have overlooked the unique characteristics of stereo-imaging tasks, leading to high decoding latency. To address this limitation, we introduce the Feature-based Cascade Alignment network (FCA-Net) to fully exploit side information to accelerate decoding. Initially, we design a feature domain patch-matching module, leveraging stereo priors, reduces redundancy in the search space and minimizes noise introduction. In the subsequent stage, we adopt an hourglass-based sparse stereo refinement network to align inter-image features with reduced computational cost. Experimental results on InStereo2K, KITTI, and Cityscapes datasets demonstrate the superiority of our approach over existing SIC methods. Notably, our approach achieves a decoding speed of 5.67 times faster than the latest DSC-based method, showcasing its efficiency in real-world applications. |
|---|---|
| AbstractList | Multi-view signal compression, particularly Stereo Image Compression (SIC), plays a pivotal role in applications such as car-mounted cameras and 3D-related scenarios. Despite the Distributed Source Coding (DSC) theory suggesting efficient compression through independent encoding and joint decoding, recent approaches have overlooked the unique characteristics of stereo-imaging tasks, leading to high decoding latency. To address this limitation, we introduce the Feature-based Cascade Alignment network (FCA-Net) to fully exploit side information to accelerate decoding. Initially, we design a feature domain patch-matching module, leveraging stereo priors, reduces redundancy in the search space and minimizes noise introduction. In the subsequent stage, we adopt an hourglass-based sparse stereo refinement network to align inter-image features with reduced computational cost. Experimental results on InStereo2K, KITTI, and Cityscapes datasets demonstrate the superiority of our approach over existing SIC methods. Notably, our approach achieves a decoding speed of 5.67 times faster than the latest DSC-based method, showcasing its efficiency in real-world applications. |
| ArticleNumber | 111799 |
| Author | Wang, Yaowei Xia, Yichong Chen, Bin Wang, Genping Wang, Haoqian Huang, Yujun |
| Author_xml | – sequence: 1 givenname: Yichong orcidid: 0009-0002-4702-5558 surname: Xia fullname: Xia, Yichong email: xiayc23@mails.tsinghua.edu.cn organization: Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China – sequence: 2 givenname: Yujun surname: Huang fullname: Huang, Yujun email: huangyj20@mails.tsinghua.edu.cn organization: Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China – sequence: 3 givenname: Bin orcidid: 0000-0002-4798-230X surname: Chen fullname: Chen, Bin email: chenbin2021@hit.edu.cn organization: Harbin Institute of Technology, Shenzhen, China – sequence: 4 givenname: Genping surname: Wang fullname: Wang, Genping email: genpingwang@163.com organization: Shenzhen Qiji Technology Co., Ltd., China – sequence: 5 givenname: Haoqian surname: Wang fullname: Wang, Haoqian email: wanghaoqian@mails.tsinghua.edu.cn organization: Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China – sequence: 6 givenname: Yaowei surname: Wang fullname: Wang, Yaowei email: wangyw@pcl.ac.cn organization: Research Center of Artificial Intelligence, Peng Cheng Laboratory, Shenzhen, China |
| BookMark | eNp9kMFKAzEURbOoYKv-gYv8wIxJZqaZcSGUYlUoutGdENLkvWlKJylJFPx7p4xrVw8u7x4uZ0FmPngg5JazkjO-vDuUJ51N6EvBRFNyzmXXzcicsYoXlWDVJVmkdGCMS16LOfncrFfFK-R7ujIGjhB1dr6nKUOEQN2ge6AmDKcIKbngad7H8NXvqdHJaAtUH13vB_CZBqTJjYnzGOIwYoK_Jheojwlu_u4V-dg8vq-fi-3b08t6tS2MaGQusOJ1y5sGOlFbxE5YrFuwKK3tsGtaaWSlm_MH1rJFRJA7VuPOCLNsUejqitQT18SQUgRUpzhOjz-KM3W2og5qsqLOVtRkZaw9TDUYt307iCoZB96AdRFMVja4_wG_9B9ytA |
| Cites_doi | 10.1016/j.patcog.2023.109696 10.1109/TCSVT.2023.3253702 10.1109/TII.2011.2174062 10.1109/TCSVT.2015.2477935 10.1109/CVPR.2018.00068 10.1109/CVPR46437.2021.01369 10.1109/CVPR.2018.00716 10.1109/CVPR46437.2021.01453 10.1109/CVPR.2015.7298925 10.1109/TIT.1976.1055508 10.1109/TIT.1973.1055037 10.1109/ICCV.2019.00323 10.1109/CVPR42600.2020.00796 10.1109/CVPR46437.2021.00154 10.1109/CVPR42600.2020.00257 10.1109/CVPR52688.2022.00074 10.1155/2020/8562323 10.1109/30.125072 10.1007/s11432-019-2803-x 10.1109/CVPR.2016.350 10.1117/1.1469618 10.1109/CVPR.2018.00567 10.1109/CVPR52688.2022.01905 10.1023/A:1008987612352 10.1016/j.patcog.2024.110632 |
| ContentType | Journal Article |
| Copyright | 2025 Elsevier Ltd |
| Copyright_xml | – notice: 2025 Elsevier Ltd |
| DBID | AAYXX CITATION |
| DOI | 10.1016/j.patcog.2025.111799 |
| DatabaseName | CrossRef |
| DatabaseTitle | CrossRef |
| DatabaseTitleList | |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Computer Science |
| ExternalDocumentID | 10_1016_j_patcog_2025_111799 S0031320325004595 |
| GroupedDBID | --K --M -D8 -DT -~X .DC .~1 0R~ 123 1B1 1RT 1~. 1~5 29O 4.4 457 4G. 53G 5VS 7-5 71M 8P~ 9JN AABNK AAEDT AAEDW AAIKJ AAKOC AALRI AAOAW AAQFI AAQXK AATTM AAXKI AAXUO AAYFN AAYWO ABBOA ABDPE ABEFU ABFNM ABFRF ABHFT ABJNI ABMAC ABWVN ABXDB ACBEA ACDAQ ACGFO ACGFS ACLOT ACNNM ACRLP ACRPL ACVFH ACZNC ADBBV ADCNI ADEZE ADJOM ADMUD ADMXK ADNMO ADTZH AEBSH AECPX AEFWE AEIPS AEKER AENEX AEUPX AFJKZ AFPUW AFTJW AGHFR AGQPQ AGUBO AGYEJ AHHHB AHJVU AHZHX AIALX AIEXJ AIGII AIIUN AIKHN AITUG AKBMS AKRWK AKYEP ALMA_UNASSIGNED_HOLDINGS AMRAJ ANKPU AOUOD APXCP ASPBG AVWKF AXJTR AZFZN BJAXD BKOJK BLXMC CS3 DU5 EBS EFJIC EFKBS EFLBG EJD EO8 EO9 EP2 EP3 F0J F5P FD6 FDB FEDTE FGOYB FIRID FNPLU FYGXN G-Q GBLVA GBOLZ HLZ HVGLF HZ~ H~9 IHE J1W JJJVA KOM KZ1 LG9 LMP LY1 M41 MO0 N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. Q38 R2- RNS ROL RPZ SBC SDF SDG SDP SDS SES SEW SPC SPCBC SST SSV SSZ T5K TN5 UNMZH VOH WUQ XJE XPP ZMT ZY4 ~G- ~HD 9DU AAYXX CITATION |
| ID | FETCH-LOGICAL-c257t-f3148155e924dff92df48edf7dd9f9587c73a58155f478fffe7b04fbc2c68f2a3 |
| ISICitedReferencesCount | 0 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001498809500003&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 0031-3203 |
| IngestDate | Sat Nov 29 07:29:07 EST 2025 Sat Oct 11 16:51:40 EDT 2025 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | Lossless compression Stereo image compression Distributed Source Coding |
| Language | English |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c257t-f3148155e924dff92df48edf7dd9f9587c73a58155f478fffe7b04fbc2c68f2a3 |
| ORCID | 0000-0002-4798-230X 0009-0002-4702-5558 |
| ParticipantIDs | crossref_primary_10_1016_j_patcog_2025_111799 elsevier_sciencedirect_doi_10_1016_j_patcog_2025_111799 |
| PublicationCentury | 2000 |
| PublicationDate | December 2025 2025-12-00 |
| PublicationDateYYYYMMDD | 2025-12-01 |
| PublicationDate_xml | – month: 12 year: 2025 text: December 2025 |
| PublicationDecade | 2020 |
| PublicationTitle | Pattern recognition |
| PublicationYear | 2025 |
| Publisher | Elsevier Ltd |
| Publisher_xml | – name: Elsevier Ltd |
| References | Misra (b29) 2019 R. Zhang, P. Isola, A.A. Efros, E. Shechtman, O. Wang, The unreasonable effectiveness of deep features as a perceptual metric, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018, pp. 586–595. Kingma, Ba (b40) 2014 Murray, Little (b2) 2000; 8 Wyner, Ziv (b11) 1976; 22 Deng, Deng, Yang, Yang, Timofte, Xu (b28) 2023; 33 Huang, Chen, Qin, Li, Wang, Dai, Xia (b14) 2023 J.-R. Chang, Y.-S. Chen, Pyramid stereo matching network, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018, pp. 5410–5418. J. Liu, S. Wang, R. Urtasun, Dsic: Deep stereo image compression, in: Proceedings of the IEEE/CVF International Conference on Computer Vision, 2019, pp. 3136–3145. Z. Shen, Y. Dai, Z. Rao, Cfnet: Cascade and fused cost volume for robust stereo matching, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2021, pp. 13906–13915. Z. Cheng, H. Sun, M. Takeuchi, J. Katto, Learned image compression with discretized gaussian mixture likelihoods and attention modules, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020, pp. 7939–7948. Bellard (b37) 2014 Zhou, Meng, Cheng (b18) 2020; 2020 M. Menze, A. Geiger, Object scene flow for autonomous vehicles, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015, pp. 3061–3070. Wallace (b20) 1992; 38 Bao, Wang, Xu, Guo, Hong, Zhang (b33) 2020; 63 Bjontegaard (b36) 2001 Fu, Du, Zhang (b26) 2024; 155 Minnen, Ballé, Toderici (b22) 2018; 31 X. Zhang, X. Zhou, M. Lin, J. Sun, Shufflenet: An extremely efficient convolutional neural network for mobile devices, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018, pp. 6848–6856. X. Gu, Z. Fan, S. Zhu, Z. Dai, F. Tan, P. Tan, Cascade cost volume for high-resolution multi-view stereo and stereo matching, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020, pp. 2495–2504. Ayzik, Avidan (b13) 2020 J. Ballé, D. Minnen, S. Singh, S.J. Hwang, N. Johnston, Variational image compression with a scale hyperprior, in: International Conference on Learning Representations, 2018. Slepian, Wolf (b10) 1973; 19 Mital, Özyılkan, Garjani, Gündüz (b12) 2022 Uchigasaki, Miyazaki, Omachi (b25) 2023; 142 J. Ballé, V. Laparra, E.P. Simoncelli, End-to-end optimized image compression, in: 5th International Conference on Learning Representations, ICLR 2017, 2017. M. Cordts, M. Omran, S. Ramos, T. Rehfeld, M. Enzweiler, R. Benenson, U. Franke, S. Roth, B. Schiele, The cityscapes dataset for semantic urban scene understanding, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016, pp. 3213–3223. Paszke, Gross, Massa, Lerer, Bradbury, Chanan, Killeen, Lin, Gimelshein, Antiga (b39) 2019; 32 Tech, Chen, Müller, Ohm, Vetro, Wang (b3) 2015; 26 Taubman, Marcellin, Rabbani (b21) 2002; 11 Li, Li, Dai, Li, Zou, Xiong (b24) 2024 M. Wödlinger, J. Kotera, J. Xu, R. Sablatnig, Sasic: Stereo image compression with latent shifts and stereo attention, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022, pp. 661–670. D. He, Y. Zheng, B. Sun, Y. Wang, H. Qin, Checkerboard context model for efficient learned image compression, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2021, pp. 14771–14780. X. Zhang, J. Shao, J. Zhang, LDMIC: Learning-based Distributed Multi-view Image Coding, in: The Eleventh International Conference on Learning Representations, 2023. Wang, Simoncelli, Bovik (b34) 2003; Vol. 2 X. Deng, W. Yang, R. Yang, M. Xu, E. Liu, Q. Feng, R. Timofte, Deep homography for efficient stereo image compression, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2021, pp. 1492–1501. Livatino, Banno, Muscato (b1) 2012; 8 J. Lei, X. Liu, B. Peng, D. Jin, W. Li, J. Gu, Deep stereo image compression via bi-directional coding, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022, pp. 19669–19678. Bégaint, Racapé, Feltman, Pushparaja (b38) 2020 Taubman (10.1016/j.patcog.2025.111799_b21) 2002; 11 10.1016/j.patcog.2025.111799_b32 10.1016/j.patcog.2025.111799_b31 Li (10.1016/j.patcog.2025.111799_b24) 2024 10.1016/j.patcog.2025.111799_b30 Bellard (10.1016/j.patcog.2025.111799_b37) 2014 Misra (10.1016/j.patcog.2025.111799_b29) 2019 Kingma (10.1016/j.patcog.2025.111799_b40) 2014 Uchigasaki (10.1016/j.patcog.2025.111799_b25) 2023; 142 Wyner (10.1016/j.patcog.2025.111799_b11) 1976; 22 Slepian (10.1016/j.patcog.2025.111799_b10) 1973; 19 Paszke (10.1016/j.patcog.2025.111799_b39) 2019; 32 Mital (10.1016/j.patcog.2025.111799_b12) 2022 Wallace (10.1016/j.patcog.2025.111799_b20) 1992; 38 Huang (10.1016/j.patcog.2025.111799_b14) 2023 10.1016/j.patcog.2025.111799_b27 10.1016/j.patcog.2025.111799_b23 Bégaint (10.1016/j.patcog.2025.111799_b38) 2020 Minnen (10.1016/j.patcog.2025.111799_b22) 2018; 31 Deng (10.1016/j.patcog.2025.111799_b28) 2023; 33 Bao (10.1016/j.patcog.2025.111799_b33) 2020; 63 Ayzik (10.1016/j.patcog.2025.111799_b13) 2020 Livatino (10.1016/j.patcog.2025.111799_b1) 2012; 8 10.1016/j.patcog.2025.111799_b5 10.1016/j.patcog.2025.111799_b4 10.1016/j.patcog.2025.111799_b7 10.1016/j.patcog.2025.111799_b6 10.1016/j.patcog.2025.111799_b19 Fu (10.1016/j.patcog.2025.111799_b26) 2024; 155 10.1016/j.patcog.2025.111799_b9 10.1016/j.patcog.2025.111799_b8 10.1016/j.patcog.2025.111799_b17 Zhou (10.1016/j.patcog.2025.111799_b18) 2020; 2020 10.1016/j.patcog.2025.111799_b16 Bjontegaard (10.1016/j.patcog.2025.111799_b36) 2001 10.1016/j.patcog.2025.111799_b15 Murray (10.1016/j.patcog.2025.111799_b2) 2000; 8 10.1016/j.patcog.2025.111799_b35 Tech (10.1016/j.patcog.2025.111799_b3) 2015; 26 Wang (10.1016/j.patcog.2025.111799_b34) 2003; Vol. 2 |
| References_xml | – volume: 8 start-page: 69 year: 2012 end-page: 77 ident: b1 article-title: 3-D integration of robot vision and laser data with semiautomatic calibration in augmented reality stereoscopic visual interface publication-title: IEEE Trans. Ind. Informatics – start-page: 699 year: 2020 end-page: 714 ident: b13 article-title: Deep image compression using decoder side information publication-title: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XVII 16 – volume: 32 year: 2019 ident: b39 article-title: Pytorch: An imperative style, high-performance deep learning library publication-title: Adv. Neural Inf. Process. Syst. – volume: 155 year: 2024 ident: b26 article-title: Hybrid-context-based multi-prior entropy modeling for learned lossless image compression publication-title: Pattern Recognit. – reference: X. Gu, Z. Fan, S. Zhu, Z. Dai, F. Tan, P. Tan, Cascade cost volume for high-resolution multi-view stereo and stereo matching, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020, pp. 2495–2504. – reference: J. Ballé, V. Laparra, E.P. Simoncelli, End-to-end optimized image compression, in: 5th International Conference on Learning Representations, ICLR 2017, 2017. – year: 2001 ident: b36 article-title: Calculation of average PSNR differences between RD-curves – start-page: 182 year: 2022 end-page: 191 ident: b12 article-title: Neural distributed image compression using common information publication-title: 2022 Data Compression Conference – year: 2024 ident: b24 article-title: Frequency-aware transformer for learned image compression publication-title: The Twelfth International Conference on Learning Representations – reference: X. Deng, W. Yang, R. Yang, M. Xu, E. Liu, Q. Feng, R. Timofte, Deep homography for efficient stereo image compression, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2021, pp. 1492–1501. – volume: Vol. 2 start-page: 1398 year: 2003 end-page: 1402 ident: b34 article-title: Multiscale structural similarity for image quality assessment publication-title: The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers, 2003 – reference: J.-R. Chang, Y.-S. Chen, Pyramid stereo matching network, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018, pp. 5410–5418. – reference: D. He, Y. Zheng, B. Sun, Y. Wang, H. Qin, Checkerboard context model for efficient learned image compression, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2021, pp. 14771–14780. – reference: M. Wödlinger, J. Kotera, J. Xu, R. Sablatnig, Sasic: Stereo image compression with latent shifts and stereo attention, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022, pp. 661–670. – year: 2019 ident: b29 article-title: Mish: A self regularized non-monotonic activation function – reference: X. Zhang, J. Shao, J. Zhang, LDMIC: Learning-based Distributed Multi-view Image Coding, in: The Eleventh International Conference on Learning Representations, 2023. – reference: J. Lei, X. Liu, B. Peng, D. Jin, W. Li, J. Gu, Deep stereo image compression via bi-directional coding, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022, pp. 19669–19678. – volume: 26 start-page: 35 year: 2015 end-page: 49 ident: b3 article-title: Overview of the multiview and 3D extensions of high efficiency video coding publication-title: IEEE Trans. Circuits Syst. Video Technol. – reference: M. Cordts, M. Omran, S. Ramos, T. Rehfeld, M. Enzweiler, R. Benenson, U. Franke, S. Roth, B. Schiele, The cityscapes dataset for semantic urban scene understanding, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016, pp. 3213–3223. – volume: 33 start-page: 6026 year: 2023 end-page: 6040 ident: b28 article-title: MASIC: Deep mask stereo image compression publication-title: IEEE Trans. Circuits Syst. Video Technol. – reference: Z. Shen, Y. Dai, Z. Rao, Cfnet: Cascade and fused cost volume for robust stereo matching, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2021, pp. 13906–13915. – volume: 22 start-page: 1 year: 1976 end-page: 10 ident: b11 article-title: The rate-distortion function for source coding with side information at the decoder publication-title: IEEE Trans. Inform. Theory – reference: R. Zhang, P. Isola, A.A. Efros, E. Shechtman, O. Wang, The unreasonable effectiveness of deep features as a perceptual metric, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018, pp. 586–595. – year: 2020 ident: b38 article-title: Compressai: a pytorch library and evaluation platform for end-to-end compression research – reference: J. Ballé, D. Minnen, S. Singh, S.J. Hwang, N. Johnston, Variational image compression with a scale hyperprior, in: International Conference on Learning Representations, 2018. – year: 2014 ident: b40 article-title: Adam: A method for stochastic optimization – volume: 63 start-page: 1 year: 2020 end-page: 11 ident: b33 article-title: Instereo2k: a large real dataset for stereo matching in indoor scenes publication-title: Sci. China Inf. Sci. – reference: X. Zhang, X. Zhou, M. Lin, J. Sun, Shufflenet: An extremely efficient convolutional neural network for mobile devices, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018, pp. 6848–6856. – reference: Z. Cheng, H. Sun, M. Takeuchi, J. Katto, Learned image compression with discretized gaussian mixture likelihoods and attention modules, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020, pp. 7939–7948. – volume: 8 start-page: 161 year: 2000 end-page: 171 ident: b2 article-title: Using real-time stereo vision for mobile robot navigation publication-title: Auton. Robots – volume: 38 start-page: xviii year: 1992 end-page: xxxiv ident: b20 article-title: The JPEG still picture compression standard publication-title: IEEE Trans. Consum. Electron. – volume: 11 start-page: 286 year: 2002 end-page: 287 ident: b21 article-title: JPEG2000: Image compression fundamentals, standards and practice publication-title: J. Electron. Imaging – reference: J. Liu, S. Wang, R. Urtasun, Dsic: Deep stereo image compression, in: Proceedings of the IEEE/CVF International Conference on Computer Vision, 2019, pp. 3136–3145. – volume: 2020 year: 2020 ident: b18 article-title: Review of stereo matching algorithms based on deep learning publication-title: Comput. Intell. Neurosci. – volume: 142 year: 2023 ident: b25 article-title: Deep image compression using scene text quality assessment publication-title: Pattern Recognit. – reference: M. Menze, A. Geiger, Object scene flow for autonomous vehicles, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015, pp. 3061–3070. – start-page: 4322 year: 2023 end-page: 4329 ident: b14 article-title: Learned distributed image compression with multi-scale patch matching in feature domain publication-title: Proceedings of the AAAI Conference on Artificial Intelligence – year: 2014 ident: b37 article-title: Bpg image format – volume: 19 start-page: 471 year: 1973 end-page: 480 ident: b10 article-title: Noiseless coding of correlated information sources publication-title: IEEE Trans. Inform. Theory – volume: 31 year: 2018 ident: b22 article-title: Joint autoregressive and hierarchical priors for learned image compression publication-title: Adv. Neural Inf. Process. Syst. – volume: 142 year: 2023 ident: 10.1016/j.patcog.2025.111799_b25 article-title: Deep image compression using scene text quality assessment publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2023.109696 – volume: 33 start-page: 6026 issue: 10 year: 2023 ident: 10.1016/j.patcog.2025.111799_b28 article-title: MASIC: Deep mask stereo image compression publication-title: IEEE Trans. Circuits Syst. Video Technol. doi: 10.1109/TCSVT.2023.3253702 – volume: 8 start-page: 69 issue: 1 year: 2012 ident: 10.1016/j.patcog.2025.111799_b1 article-title: 3-D integration of robot vision and laser data with semiautomatic calibration in augmented reality stereoscopic visual interface publication-title: IEEE Trans. Ind. Informatics doi: 10.1109/TII.2011.2174062 – volume: 26 start-page: 35 issue: 1 year: 2015 ident: 10.1016/j.patcog.2025.111799_b3 article-title: Overview of the multiview and 3D extensions of high efficiency video coding publication-title: IEEE Trans. Circuits Syst. Video Technol. doi: 10.1109/TCSVT.2015.2477935 – ident: 10.1016/j.patcog.2025.111799_b35 doi: 10.1109/CVPR.2018.00068 – ident: 10.1016/j.patcog.2025.111799_b15 – ident: 10.1016/j.patcog.2025.111799_b16 doi: 10.1109/CVPR46437.2021.01369 – volume: 31 year: 2018 ident: 10.1016/j.patcog.2025.111799_b22 article-title: Joint autoregressive and hierarchical priors for learned image compression publication-title: Adv. Neural Inf. Process. Syst. – ident: 10.1016/j.patcog.2025.111799_b30 doi: 10.1109/CVPR.2018.00716 – volume: 32 year: 2019 ident: 10.1016/j.patcog.2025.111799_b39 article-title: Pytorch: An imperative style, high-performance deep learning library publication-title: Adv. Neural Inf. Process. Syst. – ident: 10.1016/j.patcog.2025.111799_b23 doi: 10.1109/CVPR46437.2021.01453 – ident: 10.1016/j.patcog.2025.111799_b32 doi: 10.1109/CVPR.2015.7298925 – volume: 22 start-page: 1 issue: 1 year: 1976 ident: 10.1016/j.patcog.2025.111799_b11 article-title: The rate-distortion function for source coding with side information at the decoder publication-title: IEEE Trans. Inform. Theory doi: 10.1109/TIT.1976.1055508 – year: 2014 ident: 10.1016/j.patcog.2025.111799_b37 – volume: 19 start-page: 471 issue: 4 year: 1973 ident: 10.1016/j.patcog.2025.111799_b10 article-title: Noiseless coding of correlated information sources publication-title: IEEE Trans. Inform. Theory doi: 10.1109/TIT.1973.1055037 – ident: 10.1016/j.patcog.2025.111799_b6 doi: 10.1109/ICCV.2019.00323 – ident: 10.1016/j.patcog.2025.111799_b5 – ident: 10.1016/j.patcog.2025.111799_b27 doi: 10.1109/CVPR42600.2020.00796 – ident: 10.1016/j.patcog.2025.111799_b7 doi: 10.1109/CVPR46437.2021.00154 – ident: 10.1016/j.patcog.2025.111799_b17 doi: 10.1109/CVPR42600.2020.00257 – year: 2020 ident: 10.1016/j.patcog.2025.111799_b38 – ident: 10.1016/j.patcog.2025.111799_b8 doi: 10.1109/CVPR52688.2022.00074 – year: 2024 ident: 10.1016/j.patcog.2025.111799_b24 article-title: Frequency-aware transformer for learned image compression – volume: 2020 year: 2020 ident: 10.1016/j.patcog.2025.111799_b18 article-title: Review of stereo matching algorithms based on deep learning publication-title: Comput. Intell. Neurosci. doi: 10.1155/2020/8562323 – volume: 38 start-page: xviii issue: 1 year: 1992 ident: 10.1016/j.patcog.2025.111799_b20 article-title: The JPEG still picture compression standard publication-title: IEEE Trans. Consum. Electron. doi: 10.1109/30.125072 – volume: Vol. 2 start-page: 1398 year: 2003 ident: 10.1016/j.patcog.2025.111799_b34 article-title: Multiscale structural similarity for image quality assessment – volume: 63 start-page: 1 year: 2020 ident: 10.1016/j.patcog.2025.111799_b33 article-title: Instereo2k: a large real dataset for stereo matching in indoor scenes publication-title: Sci. China Inf. Sci. doi: 10.1007/s11432-019-2803-x – ident: 10.1016/j.patcog.2025.111799_b31 doi: 10.1109/CVPR.2016.350 – volume: 11 start-page: 286 issue: 2 year: 2002 ident: 10.1016/j.patcog.2025.111799_b21 article-title: JPEG2000: Image compression fundamentals, standards and practice publication-title: J. Electron. Imaging doi: 10.1117/1.1469618 – year: 2019 ident: 10.1016/j.patcog.2025.111799_b29 – start-page: 4322 year: 2023 ident: 10.1016/j.patcog.2025.111799_b14 article-title: Learned distributed image compression with multi-scale patch matching in feature domain – ident: 10.1016/j.patcog.2025.111799_b19 doi: 10.1109/CVPR.2018.00567 – ident: 10.1016/j.patcog.2025.111799_b9 doi: 10.1109/CVPR52688.2022.01905 – ident: 10.1016/j.patcog.2025.111799_b4 – volume: 8 start-page: 161 year: 2000 ident: 10.1016/j.patcog.2025.111799_b2 article-title: Using real-time stereo vision for mobile robot navigation publication-title: Auton. Robots doi: 10.1023/A:1008987612352 – start-page: 699 year: 2020 ident: 10.1016/j.patcog.2025.111799_b13 article-title: Deep image compression using decoder side information – year: 2014 ident: 10.1016/j.patcog.2025.111799_b40 – volume: 155 year: 2024 ident: 10.1016/j.patcog.2025.111799_b26 article-title: Hybrid-context-based multi-prior entropy modeling for learned lossless image compression publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2024.110632 – year: 2001 ident: 10.1016/j.patcog.2025.111799_b36 – start-page: 182 year: 2022 ident: 10.1016/j.patcog.2025.111799_b12 article-title: Neural distributed image compression using common information |
| SSID | ssj0017142 |
| Score | 2.487058 |
| Snippet | Multi-view signal compression, particularly Stereo Image Compression (SIC), plays a pivotal role in applications such as car-mounted cameras and 3D-related... |
| SourceID | crossref elsevier |
| SourceType | Index Database Publisher |
| StartPage | 111799 |
| SubjectTerms | Distributed Source Coding Lossless compression Stereo image compression |
| Title | FCA-Net: Accelerating stereo image compression through cascade alignment of side information |
| URI | https://dx.doi.org/10.1016/j.patcog.2025.111799 |
| Volume | 168 |
| WOSCitedRecordID | wos001498809500003&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVESC databaseName: Elsevier SD Freedom Collection Journals 2021 issn: 0031-3203 databaseCode: AIEXJ dateStart: 19950101 customDbUrl: isFulltext: true dateEnd: 99991231 titleUrlDefault: https://www.sciencedirect.com omitProxy: false ssIdentifier: ssj0017142 providerName: Elsevier |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV3da9swEBdbu4e9bN0X69YNPewtqDiybEl9S0PbbQ-hsI6lMDCyPkoCdUI-Rv_8nixZydoxtsFeTBBybO5-3J3Ov7tD6APPdWnAsZKslDVhSjiiqCnhlFKYrKTaqky1wyb4aCTGY3kea0-W7TgB3jTi5kbO_6uqYQ2U7Utn_0Ld6U9hAX6D0uEKaofrHyn-dDggIxsyflqDV_E6bpMGdmFnvcm1Z-l4JnlgwDZpVI9WS0-W70FkfpU4An6aZy92V006jMHsedub09fDRBLS5pP-OHBwLydgXaNvbLETs9OX6-k67R3GApHjSVr6Fved2Wbe-daYmqDFHZpHqpnZEJRaG5z3SU6z_CcbHGbr3LPnIbUwPZyDX5pdHfqHeCPPw1ClO52yv4RGlFkOYR1EqrJ4iHYpLyQYu93Bp5Px5_R5ifdZaCMfX6WrqWyJf_ef9euYZSsOudhDT-IBAg-C4p-hB7Z5jp52wzlwtNUv0PeIgyO8jQIcUIBbFOAtFOCIAhxRgBMK8MxhjwK8hYKX6OvpycXwI4mjNIgGm7wiLu_7rjyFheO2cU5S45iwxnFjpJOF4JrnqvA7HOPCOWd5nTFXa6pL4ajKX6GdZtbY1wjTWmjflDETTDFVM5EVypbSwiZpDdP7iHTCquahY0rVUQmnVRBu5YVbBeHuI95JtIpRX4jmKgDBb-988893vkWPN3g9QDurxdq-Q4_0j9VkuXgf0XILwoGAfw |
| linkProvider | Elsevier |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=FCA-Net%3A+Accelerating+stereo+image+compression+through+cascade+alignment+of+side+information&rft.jtitle=Pattern+recognition&rft.au=Xia%2C+Yichong&rft.au=Huang%2C+Yujun&rft.au=Chen%2C+Bin&rft.au=Wang%2C+Genping&rft.date=2025-12-01&rft.pub=Elsevier+Ltd&rft.issn=0031-3203&rft.volume=168&rft_id=info:doi/10.1016%2Fj.patcog.2025.111799&rft.externalDocID=S0031320325004595 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0031-3203&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0031-3203&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0031-3203&client=summon |