下划线：课题组学生，星号*：通讯作者

专著教材

[2] 郑南宁，杨勐，刘剑毅，数字信号处理简明教程习题解析（第2版），西安交通大学出版社，2022年12月。

[1] 郑南宁，杨勐，刘剑毅，数字信号处理简明教程习题解析，西安交通大学出版社，2019年4月。

技术报告

[6] Y. Li, M. Yang, et al., "LGM-Net: A Lightweight and Generalizable Network for Multi-Scale Guided Depth Super-Resolution," 2026.

[5] Y. Liu, M. Yang, et al., "DNINet: Depth Completion with Multi-Scale Depth-Normal Interaction," 2026.

[4] M. Li, L. Zhang, M. Yang, et al., "Scene Scale Prediction Network for Generalizable Monocular Depth Estimation," 2025.

[2] B. Chen, M. Yang, et al., "Joint Absolute-Relative Relation Network for Generalizable Depth Completion," 2025.

[1] X. Zhou, M. Yang, et al., "End-to-End 3D Object Detection with Depth Sructure and Location Contraints," 2023. 

近五年的代表性论文

[21] 郑南宁，杨勐，姜维周，孙宏滨，丁宁，具身智能发展趋势与展望，中国工程科学，2026年1月。[link]

[20] 郑南宁，杨勐，汪建基，蒋才桂，辛景民，人工智能本科专业大学物理课程改革与实践，计算机教育，2025年12月。[link]

[19] D. Suzhang, L. Zhang, M. Yang*, et al., "Relative RGB-Depth Structure Network for Generalizable Depth Map Recovery," 2025. [link]

[18] Z. Kuang, R. Ding, H. Wang, M. Yang*, et al., "CoIn3D: Revisiting Configuration-Invariant Multi-Camera 3D Object Detection," IEEE/CVF Computer Vision and Pattern Recognition (CVPR), Denver, Colorado, USA, June 2026. [link]

[17] Z. Kuang, R. Ding, M. Yang*, et al., "Object-Scene-Camera Decomposition and Recomposition for Data Efficient Monocular 3D Object Detection", International Journal of Computer Vision (IJCV), Jan. 2026. [link]

[16] R. Ding, Z. Kuang, M. Yang*, et al., "Multi-modal Decouple and Recouple Network for Robust 3D Object Detection," IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), Jan. 2026. [link]

[15] L. Zhang, M. Li, M. Yang*, et al., "Relative Depth Knowledge Distillation for Generalizable Monocular Depth Estimation," Neurocomputing, Jan. 2026. [link]

[14] R. Ding, Z. Kuang, M. Yang*, et al., "RayD3D: Distilling Depth Knowledge along the Ray for Robust Multi-view 3D Object Detection," AAAI Conference on Artificial Intelligence (AAAI), Singapore, Jan. 2026. [link]

[13] H. Wang, A. Xiao, X. Zhang, M. Yang*, et al., "PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency," IEEE International Conference on Computer Vision (ICCV), Honolulu, Hawaii, USA, Oct. 2025. [link]

[12] F. Li, R. Ding, M. Yang*, et al., "Consistent Feature Alignment for Cross-Modal Knowledge Distillation in Monocular 3D Object Detection," IEEE/RJS International Conference on Intelligent Robots and Systems (IROS), Hangzhou, Oct. 2025. [link]

[11] S. Liu, D. Suzhang, M. Yang*, et al., "Depth Map Super-Resolution via Deep Cross-modality and Cross-scale Guidance," IEEE Transactions on Multimedia (TMM), Mar. 2025. [link]

[10] H. Wang, M. Yang*, et al., "Scale Propagation Network for Generalizable Depth Completion," IEEE Transactions on Pattern Analsis and Machine Intelligence (T-PAMI), 2025. [link]

[9] C. Wei, M. Yang*, et al., "FS-Depth: Focal-and-Scale Depth Estimation from a Single Image in Unseen Indoor Scene," IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), Nov. 2024. [link]

[8] R. Ding, M. Yang*, et al., "Selective Transfer Learning of Cross-Modality Distillation for Monocular 3D Object Detection," IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), Oct. 2024. [link]

[7] H. Wang, M. Yang*, et al., "G2-MonoDepth: A General Framework of Generalized Depth Inference from Monocular RGB-X Data," IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), May 2024. [link]

[6] M. Yang*, L. Zhang, D. Suzhang, C. Zhu, and N. Zheng, "Misaligned RGB-Depth Boundary Identification and Correction for Depth Image Recovery," IEEE Transactions on Broadcasting (TBC), Mar. 2024. [link]

[5] H. Wang, M. Yang*, C. Zhu, and N. Zheng, "RGB-Guided Depth Map Recovery by Two-Stage Coarse-to-Fine Dense CRF Models,"  IEEE Transactions on Image Processing (TIP), Jan. 2023. [link]

[4] D. Ren, M. Yang*, J. Wu, et al., "Surface Normal and Gaussian Weight Constraints for Indoor Depth Structure Completion," Pattern Recognition (PR), Jan. 2023. [link]

[3] H. Wang, M. Yang*, X. Lan, C. Zhu, and N. Zheng, "Depth Map Recovery based on a Unified Depth Boundary Distortion Model," IEEE Transactions on Image Processing (TIP), 2022. [link]

[2] M. Yang, C. Zhu, X. Lan, and N. Zheng, "Efficient Estimation of View Synthesis Distortion for Depth Coding Optimization," IEEE Transactions on Multimedia (TMM), Apr. 2019. [link]

[1] M. Yang and N. Zheng. "SynBF: A New Bilateral Filter for Post-removal of Noise from Synthesis Views in 3D Video," IEEE Transactions on Multimedia (TMM), Jan. 2019. [link]

授权发明专利

[10] 杨勐，邝兆年，丁瑞，郑南宁，“一种用于单目3D目标检测的数据增强方法及系统”，申请号：2024119412721，2024年12月26日。（已授权）

[9] 杨勐，周祥，丁瑞，郑南宁，“一种基于平面约束与位置约束的3D目标检测方法及系统”，申请号：202310028861.X，2022。（已授权）

[8] 杨勐，任东冉，郑南宁，“一种弱对齐RGB-D图像引导的深度图补全方法及系统”，申请号：202211064275.2，2022年8月31日。（已授权）

[7] 杨勐，任东冉，郑南宁，“一种基于法向量和高斯权重约束的深度图像补全方法及系统”，申请号：ZL202110574430.4，2021年5月。（已授权）

[6] 杨勐，王昊天，郑南宁，”基于两层全连接条件随机场模型的深度图结构修复方法“，申请号：ZL202111057715.2，2021年11月。（已授权）

[5] 杨勐，王昊天，郑南宁，“一种基于RGB-D的SSIM结构相似度的迭代深度图结构修复方法”，申请号：ZL200010007508.X，2020年1月。(已授权)

[4] 杨勐，陈翔，光宇杰，郑南宁，“一种基于引导滤波器的鲁棒深度图结构重建和去噪方法”，申请号：ZL202010007506.0，2020年1月。(已授权)

[3] 杨勐，郝鹏程，王爽，郑南宁，“一种基于显著性前景内容的低光照图像增强方法”，申请号：ZL202010056934.2，2020年1月16日。(已授权)

[2] 杨勐，马勇，郑南宁，“一种基于单视点RGB-D图像的大尺度全景视点合成方法”，申请号：ZL202010113813.7，2020年2月24日。(已授权)

[1] 杨勐，光宇杰，成钰，郑南宁，“一种基于彩色图引导的深度图恢复及视点合成优化方法”，申请号：ZL201810600927.7，2018年6月。（已授权）