光电与智能研究院

科研成果

每年的科研成果 2003 2020 2021 2022 2023 2024 2025 2025

• 1249 文章
• 305 会议稿件
• 31 会议文章
• 27 论文
• 39 更多
  • 14 文献综述
  • 10 快报
  • 7 社论
  • 4 评论/辩论
  • 3 短篇评述
  • 1 章节

每年的科研成果

每年的科研成果

搜索结果

• 2025

  Edge Contrastive Learning: An Augmentation-Free Graph Contrastive Learning Model

  Li, Y., Zhang, H. & Yuan, Y., 11 4月 2025, 在: Proceedings of the AAAI Conference on Artificial Intelligence. 39, 17, 页码 18575-18583 9 页码

  科研成果: 期刊稿件 › 会议文章 › 同行评审

  • Contrastive Learning 100%
  • Graph Contrastive Learning 100%
  • Experimental Result 14%
  • Graph Neural Network 14%
  • Learning Scheme 14%

• Enhancing Low-Rank Adaptation with Recoverability-Based Reinforcement Pruning for Object Counting

  Guo, H., Gao, J. & Yuan, Y., 11 4月 2025, 在: Proceedings of the AAAI Conference on Artificial Intelligence. 39, 3, 页码 3238-3246 9 页码

  科研成果: 期刊稿件 › 会议文章 › 同行评审

  • Similarity 100%
  • Multiscale 100%
  • Reinforcement Learning 100%
  • Network Parameter 100%
  • Scale Feature 100%

• Learning 2D Invariant Affordance Knowledge for 3D Affordance Grounding

  Gao, X., Zhang, P., Qu, D., Wang, D., Wang, Z., Ding, Y. & Zhao, B., 11 4月 2025, 在: Proceedings of the AAAI Conference on Artificial Intelligence. 39, 3, 页码 3095-3103 9 页码

  科研成果: 期刊稿件 › 会议文章 › 同行评审

  • Wide Range 100%
  • Geometric Structure 100%
  • Data Mining 100%
  • Object Affordances 100%
• 2024

  Color Event Enhanced Single-Exposure HDR Imaging

  Cui, M., Wang, Z., Wang, D., Zhao, B. & Li, X., 25 3月 2024, 在: Proceedings of the AAAI Conference on Artificial Intelligence. 38, 2, 页码 1399-1407 9 页码

  科研成果: 期刊稿件 › 会议文章 › 同行评审

  • Dynamic Range 100%
  • Tone Mapping 33%
  • Joints (Structural Components) 11%
  • Lighting Condition 11%
  • Color Change 11%
  4 引用 （Scopus）

• Combating Data Imbalances in Federated Semi-supervised Learning with Dual Regulators

  Bai, S., Li, S., Zhuang, W., Zhang, J., Yang, K., Hou, J., Zhang, S., Yi, S. & Gao, J., 25 3月 2024, 在: Proceedings of the AAAI Conference on Artificial Intelligence. 38, 10, 页码 10989-10997 9 页码

  科研成果: 期刊稿件 › 会议文章 › 同行评审

  开放访问

  • Semisupervised Learning 100%
  • Unlabeled Data 40%
  • Data Distribution 40%
  • Learning Framework 20%
  • Training Model 20%
  4 引用 （Scopus）

• DAG-Aware Variational Autoencoder for Social Propagation Graph Generation

  Hou, D., Gao, C., Li, X. & Wang, Z., 25 3月 2024, 在: Proceedings of the AAAI Conference on Artificial Intelligence. 38, 8, 页码 8508-8516 9 页码

  科研成果: 期刊稿件 › 会议文章 › 同行评审

  • Attribute Data 100%
  • Social Phenomenon 100%
  • Propagation Network 100%
  4 引用 （Scopus）

• GS-SLAM: Dense Visual SLAM with 3D Gaussian Splatting

  Yan, C., Qu, D., Xu, D., Zhao, B., Wang, Z., Wang, D. & Li, X., 2024, 在: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 页码 19595-19604 10 页码

  科研成果: 期刊稿件 › 会议文章 › 同行评审

  开放访问

  • Simultaneous localization and mapping 100%
  • Tracking Process 20%
  • Rendering Pipeline 20%
  • Implicit Representation 20%
  51 引用 （Scopus）

• HPL-ESS: Hybrid Pseudo-Labeling for Unsupervised Event-based Semantic Segmentation

  Jing, L., Ding, Y., Gao, Y., Wang, Z., Yan, X., Wang, D., Schaefer, G., Fang, H., Zhao, B. & Li, X., 2024, 在: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 页码 23128-23137 10 页码

  科研成果: 期刊稿件 › 会议文章 › 同行评审

  开放访问

  • Image Segmentation 100%
  • Image Reconstruction 66%
  • Unsupervised Domain Adaptation 33%
  • Confirmation Bias 33%
  • Supervised Method 33%
  4 引用 （Scopus）

• Implicit Event-RGBD Neural SLAM

  Qu, D., Yan, C., Wang, D., Yin, J., Chen, Q., Xu, D., Zhang, Y., Zhao, B. & Li, X., 2024, 在: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 页码 19584-19594 11 页码

  科研成果: 期刊稿件 › 会议文章 › 同行评审

  开放访问

  • Experimental Result 100%
  • Optimization Strategy 100%
  • Response Function 100%
  • temporal difference 100%
  • Implicit Representation 100%
  5 引用 （Scopus）

• KOI: Accelerating Online Imitation Learning via Hybrid Key-state Guidance

  Lu, J., Xia, W., Wang, D., Wang, Z., Zhao, B., Hu, D. & Li, X., 2024, 在: Proceedings of Machine Learning Research. 270, 页码 3847-3865 19 页码

  科研成果: 期刊稿件 › 会议文章 › 同行评审

  • Language Modeling 100%
  • Motion Capture 100%
  • Visual Language 100%

• Multi-Class Support Vector Machine with Maximizing Minimum Margin

  Nie, F., Hao, Z. & Wang, R., 25 3月 2024, 在: Proceedings of the AAAI Conference on Artificial Intelligence. 38, 13, 页码 14466-14473 8 页码

  科研成果: 期刊稿件 › 会议文章 › 同行评审

  开放访问

  • Support Vector Machine 100%
  • Multiobjective Optimization 20%
  • Pattern Recognition 20%
  • Optimization Strategy 20%
  • Classification Method 20%
  7 引用 （Scopus）

• Outlier-Robust Feature Selection with ℓ_2,1-Norm Minimization and Group Row-Sparsity Induced Constraints

  Wang, J., Wang, Z., Wang, R., Nie, F. & Li, X., 2024, 在: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. 页码 3585-3589 5 页码

  科研成果: 期刊稿件 › 会议文章 › 同行评审

  • Feature Extraction 100%
  • Sparsity 100%
  • Feature Selection 100%
  • Selection Method 66%
  • Gaussians 33%

• Point-PEFT: Parameter-Efficient Fine-Tuning for 3D Pre-trained Models

  Tang, Y., Zhang, R., Guo, Z., Ma, X., Zhao, B., Wang, Z., Wang, D. & Li, X., 25 3月 2024, 在: Proceedings of the AAAI Conference on Artificial Intelligence. 38, 6, 页码 5171-5179 9 页码

  科研成果: 期刊稿件 › 会议文章 › 同行评审

  开放访问

  • Pre-Trained Model 100%
  • Point Cloud 50%
  • Free Parameter 25%
  • Multimodality 25%
  • Geometric Information 25%
  7 引用 （Scopus）
• 2023

  Behavior Contrastive Learning for Unsupervised Skill Discovery

  Yang, R., Bai, C., Guo, H., Li, S., Zhao, B., Wang, Z., Liu, P. & Li, X., 2023, 在: Proceedings of Machine Learning Research. 202, 页码 39183-39204 22 页码

  科研成果: 期刊稿件 › 会议文章 › 同行评审

  • Objective Maximize 100%
  12 引用 （Scopus）

• Cross-Domain Policy Adaptation via Value-Guided Data Filtering

  Xu, K., Bai, C., Ma, X., Wang, D., Zhao, B., Wang, Z., Li, X. & Li, W., 2023, 在: Advances in Neural Information Processing Systems. 36

  科研成果: 期刊稿件 › 会议文章 › 同行评审

  • Data Filtering 100%
  • Dynamic Adaptation 50%
  • Superior Performance 50%
  • Reinforcement Learning 50%
  • Source Domain Data 50%
  7 引用 （Scopus）

• Diffusion Model is an Effective Planner and Data Synthesizer for Multi-Task Reinforcement Learning

  He, H., Bai, C., Xu, K., Yang, Z., Zhang, W., Wang, D., Zhao, B. & Li, X., 2023, 在: Advances in Neural Information Processing Systems. 36

  科研成果: 期刊稿件 › 会议文章 › 同行评审

  • Single Demonstration 100%
  25 引用 （Scopus）

• Joint Feature and Differentiable k-NN Graph Learning using Dirichlet Energy

  Xu, L., Chen, L., Wang, R., Nie, F. & Li, X., 2023, 在: Advances in Neural Information Processing Systems. 36

  科研成果: 期刊稿件 › 会议文章 › 同行评审

  • Feature Selection 100%
  • k-Nearest Neighbors Algorithm 100%
  • Feature Extraction 66%
  • Neural Network 33%
  • Machine Learning 33%
  1 引用 （Scopus）

• Propagate and Calibrate: Real-Time Passive Non-Line-of-Sight Tracking

  Wang, Y., Wang, Z., Zhao, B., Wang, D., Chen, M. & Li, X., 2023, 在: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2023-June, 页码 972-981 10 页码

  科研成果: 期刊稿件 › 会议文章 › 同行评审

  开放访问

  • Granularity Level 100%
  • Application Scenario 100%
  • Synthetic Data 100%
  • Real Application 100%
  1 引用 （Scopus）

• Unsupervised Feature Selection with self-Weighted and ℓ_2,0-Norm Constraint

  Yuan, Y., Wang, Z., Nie, F. & Li, X., 2023, 在: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings.

  科研成果: 期刊稿件 › 会议文章 › 同行评审

  • Structure Matrix 100%
  5 引用 （Scopus）
• 2021

  3D confocal photoacoustic dermoscopy using a multifunctional sono-opto probe

  Ma, H., Ding, R. & Huang, Q., 2021, 在: IEEE International Ultrasonics Symposium, IUS.

  科研成果: 期刊稿件 › 会议文章 › 同行评审

  • Pathophysiology 100%
  • Skin Disease 100%
  2 引用 （Scopus）
• 2020

  Efficient clustering based on a unified view of k-means and ratio-cut

  Pei, S., Nie, F., Wang, R. & Li, X., 2020, 在: Advances in Neural Information Processing Systems. 2020-December

  科研成果: 期刊稿件 › 会议文章 › 同行评审

  • Clustering Algorithm 100%
  • Time Complexity 33%
  • Clustering Method 33%
  • Synthetic Datasets 33%
  • Spectral Clustering 33%
  23 引用 （Scopus）

• Efficient dynamic scene deblurring using spatially variant deconvolution network with optical flow guided training

  Yuan, Y., Su, W. & Ma, D., 2020, 在: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 页码 3552-3561 10 页码, 9157149.

  科研成果: 期刊稿件 › 会议文章 › 同行评审

  • Image Restoration Problem 100%
  • Fixed Structure 66%
  • Fixed Parameter 66%
  • Fitting Capability 66%
  108 引用 （Scopus）

• Learning feature sparse principal subspace

  Tian, L., Nie, F., Wang, R. & Li, X., 2020, 在: Advances in Neural Information Processing Systems. 2020-December

  科研成果: 期刊稿件 › 会议文章 › 同行评审

  • Representation Learning 100%
  • Sparsity 100%
  • Approximation (Algorithm) 40%
  • Experimental Result 20%
  • Feature Extraction 20%
  18 引用 （Scopus）

• Predicting cognitive declines using longitudinally enriched representations for imaging biomarkers

  Alzheimer’s Disease Neuroimaging Initiative, 2020, 在: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 页码 4826-4835 10 页码, 9156727.

  科研成果: 期刊稿件 › 会议文章 › 同行评审

  • High Throughput 100%
  • Performance Gain 100%
  • Prediction Model 100%
  • Biggest Challenge 100%
  • Neuroimaging Study 100%
  7 引用 （Scopus）

• Unsupervised semantic aggregation and deformable template matching for semi-supervised learning

  Han, T., Gao, J., Yuan, Y. & Wang, Q., 2020, 在: Advances in Neural Information Processing Systems. 2020-December

  科研成果: 期刊稿件 › 会议文章 › 同行评审

  • Semisupervised Learning 100%
  • Template Matching 100%
  • Unlabeled Data 75%
  • Semantic Label 50%
  • Classification Performance 25%
  20 引用 （Scopus）

• Variational context-deformable convnets for indoor scene parsing

  Xiong, Z., Yuan, Y., Guo, N. & Wang, Q., 2020, 在: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 页码 3991-4001 11 页码, 9156787.

  科研成果: 期刊稿件 › 会议文章 › 同行评审

  • Probabilistic Modeling 100%
  60 引用 （Scopus）
• 2017

  Learning A structured optimal bipartite graph for co-clustering

  Nie, F., Wang, X., Deng, C. & Huang, H., 2017, 在: Advances in Neural Information Processing Systems. 2017-December, 页码 4130-4139 10 页码

  科研成果: 期刊稿件 › 会议文章 › 同行评审

  • Clustering Method 100%
  • Bipartite Graph 100%
  • Clustering Result 50%
  • Cluster Structure 50%
  • Postprocessing 25%
  128 引用 （Scopus）
• 2016

  Avoiding optimal mean robust PCA/2DPCA with non-greedy ℓ₁-norm maximization

  Luo, M., Nie, F., Chang, X., Yang, Y., Hauptmann, A. & Zheng, Q., 2016, 在: IJCAI International Joint Conference on Artificial Intelligence. 2016-January, 页码 1802-1808 7 页码

  科研成果: 期刊稿件 › 会议文章 › 同行评审

  • Principal Component 100%
  • Component Analysis 100%
  • Principal Component Analysis 100%
  • Experimental Result 11%
  • Computational Complexity 11%
  42 引用 （Scopus）

• Parameter-free auto-weighted multiple graph learning: A framework for multiview clustering and semi-supervised classification

  Nie, F., Li, J. & Li, X., 2016, 在: IJCAI International Joint Conference on Artificial Intelligence. 2016-January, 页码 1881-1887 7 页码

  科研成果: 期刊稿件 › 会议文章 › 同行评审

  • Free Parameter 100%
  • Semisupervised Learning 100%
  • Supervised Classification 100%
  • Supervised Learning 100%
  • World Application 50%
  641 引用 （Scopus）

• Robust and sparse fuzzy k-means clustering

  Xu, J., Han, J., Kai, X. & Nie, F., 2016, 在: IJCAI International Joint Conference on Artificial Intelligence. 2016-January, 页码 2224-2230 7 页码

  科研成果: 期刊稿件 › 会议文章 › 同行评审

  • k-means Clustering 100%
  • Clustering Algorithm 100%
  • Performance Degradation 50%
  • Experimental Result 50%
  • Sparsity 50%
  126 引用 （Scopus）
• 2014

  In defense of iterated conditional mode for hyperspectral image classification

  Lin, J., Wang, Q. & Yuan, Y., 3 9月 2014, 在: Proceedings - IEEE International Conference on Multimedia and Expo. 2014-September, Septmber, 6890171.

  科研成果: 期刊稿件 › 会议文章 › 同行评审

  • Hyperspectral Image 100%
  • Image Classification 100%
  • Hyperspectral Image Classification 100%
  • State of the Art 66%
  • State-of-the-Art Method 50%
  12 引用 （Scopus）