Computer Science ›› 2025, Vol. 52 ›› Issue (10): 144-150.doi: 10.11896/jsjkx.240800159
• Computer Graphics & Multimedia • Previous Articles Next Articles
WEN Jing, ZHANG Songsong, LI Xufeng
CLC Number:
[1]VOULODIMOS A,DOULAMIS N,DOULAMIS A,et al.Deep learning for computer vision:A brief review[J].Computational Intelligence and Neuroscience,2018,2018(1):1-13. [2]BERTINETTO L,VALMADRE J,HENRIQUES J F,et al.Fully-convolutional siamese networks for object tracking[C]//ECCV 2016 Workshops.Springer,2016:850-865. [3]LI B,YAN J,WU W,et al.High performance visual tracking with siamese region proposal network[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.New York:IEEE,2018:8971-8980. [4]VASWANI A,SHAZEER N,PARMAR N,et al.Attention isall you need[C]//Proceedings of the 31st International Confe-rence on Neural Information Processing Systems.2017:6000-6010. [5]CHEN X,PENG H,WANG D,et al.Seqtrack:Sequence to sequence learning for visual object tracking[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.New York:IEEE,2023:14572-14581. [6]DOSOVITSKIY A.An image is worth 16x16 words:Transformers for image recognition at scale[C]//Proceedings of the International Conference on Learning Representations.2021. [7]WANG N,ZHOU W,WANG J,et al.Transformer meets trac-ker:Exploiting temporal context for robust visual tracking[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.New York:IEEE,2021:1571-1580. [8]CHEN X,YAN B,ZHU J,et al.Transformer tracking[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.New York:IEEE,2021:8126-8135. [9]YU B,TANG M,ZHENG L,et al.High-performance discriminative tracking with transformers[C]//Proceedings of the IEEE/CVF International Conference on Computer Vision.New York:IEEE,2021:9856-9865. [10]YAN B,PENG H,FU J,et al.Learning spatio-temporal transformer for visual tracking[C]//Proceedings of the IEEE/CVF International Conference on Computer Vision.New York:IEEE,2021:10448-10457. [11]ZHENG Y,ZHONG B,LIANG Q,et al.Odtrack:Online dense temporal token learning for visual tracking[C]//Proceedings of the AAAI Conference on Artificial Intelligence.AAAI,2024:7588-7596. [12]WEI X,BAI Y,ZHENG Y,et al.Autoregressive visual tracking[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition,New York:IEEE,2023:9697-9706. [13]XIA C,WANG X,LYU F,et al.Vit-comer:Vision transformer with convolutional multi-scale feature interaction for dense predictions[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.New York:IEEE,2024:5493-5502. [14]CHEN M M.Research on Object Tracking Algorithm Integra-ting Swin Transformer Multi-scale Features and Pooling Spatial Features[J].Journal of Chongqing Technology and Business University.Natural Science Edition,2025,42(3):110-117. [15]XU W,WAN Y.ELA:Efficient Local Attention for Deep Conv-olutional Neural Networks[J].arXiv:2403.01123,2024. [16]ZHU X,SU W,LU L,et al.Deformable DETR:Deformabletransformers for end-to-end object detection[C]//Proceedings of the International Conference on Learning Representations.2021. [17]CHEN T,SAXENA S,LI L,et al.Pix2seq:A language modeling framework for object detection [C]//Proceedings of the International Conference on Learning Representations.2022. [18]DE BOER P T,KROESE D P,MANNOR S,et al.A tutorial on the cross-entropy method[J].Annals of Operations Research,2005,134(1):19-67. [19]GEVORGYAN Z.SIoU loss:More powerful learning for bounding box regression[J].arXiv:2303.15067,2023. [20]HUANG L,ZHAO X,HUANG K.Got-10k:A large high-diver-sity benchmark for generic object tracking in the wild[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2019,43(5):1562-1577. [21]FAN H,LIN L,YANG F,et al.Lasot:A high-quality benchmark for large-scale single object tracking[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.New York:IEEE,2019:5374-5383. [22]MUELLER M,SMITH N,GHANEM B.A Benchmark andSimulator for UAV Tracking[C]//ECCV 2016 Workshops.Springer,2016:445-461. [23]LI B,WU W,WANG Q,et al.Siamrpn++:Evolution of siamese visual tracking with very deep networks[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.New York:IEEE,2019:4282-4291. [24]BHAY G,DANELLJAN M,GOOL L V,et al.Learning dis-criminative model prediction for tracking[C]//Proceedings of the IEEE/CVF International Conference on Computer Cision.New York:IEEE,2019:6182-6191. [25]ZHANG Z,PENG H,FU J,et al.Ocean:Object-aware anchor-free tracking[C]//Computer Vision ECCV.Berlin:Springer,2020:771-787. [26]DANELLJAN M,GOOL L V,TIMOFTE R.Probabilistic re-gression for visual tracking[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.New York:IEEE,2020:7183-7192. [27]VOIGTLAENDER P,LUITEN J,TORR P H S,et al.SiamR-CNN:Visual tracking by re-detection[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.New York:IEEE,2020:6578-6588. [28]FU Z,FU Z,LIU Q,et al.SparseTT:Visual tracking withsparse transformers[C]//Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence.AAAI,2022:905-912. [29]ZHANG Z,LIU Y,WANG X,et al.Learn to match:Automatic matching network design for visual tracking[C]//Proceedings of the IEEE/CVF International Conference on Computer Vision.New York:IEEE,2021:13339-13348. [30]LIN L,FAN H,ZHANG Z,et al.Swintrack:A simple andstrong baseline for transformer tracking[C]//Proceedings of Advances in Neural Information Processing Systems.2022:16743-16754. [31]CUI Y,JIANG C,WANG L,et al.Mixformer:End-to-end tracking with iterative mixed attention[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.New York:IEEE,2022:13608-13618. [32]YE B,CHANG H,MA B,et al.Joint feature learning and relation modeling for tracking:A one-stream framework[C]//European Conference on Computer Vision.Berlin:Springer,2022:341-357. [33]CAI Y,LIU J,TANG J,et al.Robust object modeling for visualtracking[C]//Proceedings of the IEEE/CVF International Conference on Computer Vision.New York:IEEE,2023:9589-9600. [34]XU Y,WANG Z,LI Z,et al.SiamFC++:Towards robust and accurate visual tracking with target estimation guidelines [C]//Proceedings of the AAAI Conference on Artificial Intelligence.AAAI,2020:12549-12556. |
[1] | WANG Baocai, WU Guowei. Interpretable Credit Risk Assessment Model:Rule Extraction Approach Based on AttentionMechanism [J]. Computer Science, 2025, 52(10): 50-59. |
[2] | ZHENG Hanyuan, GE Rongjun, HE Shengji, LI Nan. Direct PET to CT Attenuation Correction Algorithm Based on Imaging Slice Continuity [J]. Computer Science, 2025, 52(10): 115-122. |
[3] | XU Hengyu, CHEN Kun, XU Lin, SUN Mingzhai, LU Zhou. SAM-Retina:Arteriovenous Segmentation in Dual-modal Retinal Image Based on SAM [J]. Computer Science, 2025, 52(10): 123-133. |
[4] | SHENG Xiaomeng, ZHAO Junli, WANG Guodong, WANG Yang. Immediate Generation Algorithm of High-fidelity Head Avatars Based on NeRF [J]. Computer Science, 2025, 52(10): 159-167. |
[5] | ZHENG Dichen, HE Jikai, LIU Yi, GAO Fan, ZHANG Dengyin. Low Light Image Adaptive Enhancement Algorithm Based on Retinex Theory [J]. Computer Science, 2025, 52(10): 168-175. |
[6] | RUAN Ning, LI Chun, MA Haoyue, JIA Yi, LI Tao. Review of Quantum-inspired Metaheuristic Algorithms and Its Applications [J]. Computer Science, 2025, 52(10): 190-200. |
[7] | XIONG Zhuozhi, GU Zhouhong, FENG Hongwei, XIAO Yanghua. Subject Knowledge Evaluation Method for Language Models Based on Multiple ChoiceQuestions [J]. Computer Science, 2025, 52(10): 201-207. |
[8] | WANG Jian, WANG Jingling, ZHANG Ge, WANG Zhangquan, GUO Shiyuan, YU Guiming. Multimodal Information Extraction Fusion Method Based on Dempster-Shafer Theory [J]. Computer Science, 2025, 52(10): 208-216. |
[9] | CHEN Yuyan, JIA Jiyuan, CHANG Jingwen, ZUO Kaiwen, XIAO Yanghua. SPEAKSMART:Evaluating Empathetic Persuasive Responses by Large Language Models [J]. Computer Science, 2025, 52(10): 217-230. |
[10] | LI Sihui, CAI Guoyong, JIANG Hang, WEN Yimin. Novel Discrete Diffusion Text Generation Model with Convex Loss Function [J]. Computer Science, 2025, 52(10): 231-238. |
[11] | ZHANG Jiawei, WANG Zhongqing, CHEN Jiali. Multi-grained Sentiment Analysis of Comments Based on Text Generation [J]. Computer Science, 2025, 52(10): 239-246. |
[12] | CHEN Jiahao, DUAN Liguo, CHANG Xuanwei, LI Aiping, CUI Juanjuan, HAO Yuanbin. Text Sentiment Classification Method Based on Large-batch Adversarial Strategy and EnhancedFeature Extraction [J]. Computer Science, 2025, 52(10): 247-257. |
[13] | WANG Ye, WANG Zhongqing. Text Simplification for Aspect-based Sentiment Analysis Based on Large Language Model [J]. Computer Science, 2025, 52(10): 258-265. |
[14] | ZHAO Jinshuang, HUANG Degen. Summary Faithfulness Evaluation Based on Data Augmentation and Two-stage Training [J]. Computer Science, 2025, 52(10): 266-274. |
[15] | SUN Liangxu, LI Linlin, LIU Guoli. Sub-problem Effectiveness Guided Multi-objective Evolution Algorithm [J]. Computer Science, 2025, 52(10): 296-307. |
|