Yuntao Qian
教授
Works on hyperspectral imaging, remote-sensing image processing, signal processing and machine learning.
Yuntao Qian's lab at Zhejiang works on computational imaging & photography, signal processing & information theory and speech enhancement & signal processing. 42 papers since 2023, 6 at top venues, mostly CVPR and ICASSP. Applications close .
At a glance
- papers, 2023–2026
- 11/ year
- at T1 venues
- 14%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom DBLP, 2023–2026
- 3 papers2026 · T1 2 · collecting
- 8 papers2025 · T1 2
- 15 papers2024 · T1 1
- 16 papers2023 · T1 1
T1 venuesOtherVenues: CVPR, ICASSP, Pattern Recognition, TIP, ICME
Research focuspaper titles that use each topic's words
- Computational imaging & photography0 papers
- Signal processing & information theory0 papers
- Speech enhancement & signal processing0 papers
- processing0 papers
- image processing0 papers
Paper list
From DBLP.
20263 papers
- CVPR (T1)Balanced Hierarchical Contrastive Learning with Decoupled Queries for Fine-grained Object Detection in Remote Sensing Images (opens in a new tab)
- Pattern RecognitionBridging the resolution gap: Semantic-aware alignment for cross-resolution change detection (opens in a new tab)
- CVPR (T1)HierUQ: Hierarchical Uncertainty Quantification with Adaptive Granularity Reconciliation for Degraded Image Classification (opens in a new tab)
20258 papers
- IEEE Trans. Geosci. Remote. Sens.Frequency- and Spatial-Domain Saliency Network for Remote Sensing Cross-Modal Retrieval (opens in a new tab)
- IEEE Trans. Geosci. Remote. Sens.Hierarchical Contrastive Learning for Multigranularity Ship Classification With Learnable Class Queries (opens in a new tab)
- Appl. Intell.Incremental classification of remote sensing images using feature pyramid and class hierarchy enhanced by label relationship graphs (opens in a new tab)
- ICASSP (T1)Label Relationship Graph-Enhanced Class Hierarchy for Incremental Classification of Remote Sensing Images (opens in a new tab)
- Pattern RecognitionMulti-domain universal representation learning for hyperspectral object tracking (opens in a new tab)
- IEEE Trans. Geosci. Remote. Sens.Spatial-Spectral-Temporal Correlation Filter for Hyperspectral Object Tracking (opens in a new tab)
- TIP (T1)SUIT: Spatial-Spectral Union-Intersection Interaction Network for Hyperspectral Object Tracking (opens in a new tab)
- IEEE Trans. Geosci. Remote. Sens.Whole Semantic Sparse Coding Network for Remote Sensing Image-Text Retrieval (opens in a new tab)
202415 papers
- Int. J. Wavelets Multiresolution Inf. Process.A survey on deep learning-based spatio-temporal action detection (opens in a new tab)
- IEEE Trans. Geosci. Remote. Sens.Adaptive Graph Modeling With Self-Training for Heterogeneous Cross-Scene Hyperspectral Image Classification (opens in a new tab)
- IEEE Trans. Geosci. Remote. Sens.Building Cross-Domain Mapping Chains From Multi-CycleGAN for Hyperspectral Image Classification (opens in a new tab)
- IEEE Trans. Geosci. Remote. Sens.Diffusion-Model-Based Hyperspectral Unmixing Using Spectral Prior Distribution (opens in a new tab)
- IEEE Trans. Geosci. Remote. Sens.Discriminative Vision Transformer for Heterogeneous Cross-Domain Hyperspectral Image Classification (opens in a new tab)
- IEEE Trans. Circuits Syst. Video Technol.Efficiently Exploiting Spatially Variant Knowledge for Video Deblurring (opens in a new tab)
- IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens.Fine-Grained Image Recognition Methods and Their Applications in Remote Sensing Images: A Review (opens in a new tab)
- IEEE Trans. Geosci. Remote. Sens.Hyperspectral Image Denoising via Spatial-Spectral Recurrent Transformer (opens in a new tab)
- IGARSSIncremental Classification of Remote Sensing Images with Feature Pyramid and Class Hierarchy (opens in a new tab)
- IEEE Trans. Geosci. Remote. Sens.Iterative Low-Rank Network for Hyperspectral Image Denoising (opens in a new tab)
- IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens.Mask-Guided Local-Global Attentive Network for Change Detection in Remote Sensing Images (opens in a new tab)
- IEEE Trans. Geosci. Remote. Sens.Material-Guided Multiview Fusion Network for Hyperspectral Object Tracking (opens in a new tab)
202316 papers
- IGARSSA Noise-Model-Free Hyperspectral Image Denoising Method Based on Diffusion Model (opens in a new tab)
- Int. J. Wavelets Multiresolution Inf. Process.An aggressive reduction on the complexity of optimization for non-strongly convex objectives (opens in a new tab)
- IEEE Trans. Geosci. Remote. Sens.Ca-STANet: Spatiotemporal Attention Network for Chlorophyll-a Prediction With Gap-Filled Remote Sensing Data (opens in a new tab)
- WHISPERSCross-Domain Heterogeneous Hyperspectral Image Classification Based on Meta-Learning with Task-Adaptive Loss Function (opens in a new tab)
- IGARSSCross-Domain Hyperspectral Image Classification Based on Graph Convolutional Networks (opens in a new tab)
- IGARSSCross-Domain Hyperspectral Image Classification Based on Transformer (opens in a new tab)
- Int. J. Wavelets Multiresolution Inf. Process.Cross-domain residual deep NMF for transfer learning between different hyperspectral image scenes (opens in a new tab)
- IEEE Trans. Geosci. Remote. Sens.Deep Parameterized Neural Networks for Hyperspectral Image Denoising (opens in a new tab)
- IET Comput. Vis.Domain-invariant attention network for transfer learning between cross-scene hyperspectral images (opens in a new tab)
- IGARSSHierarchical Superpixel Relation Graph Combined with Convolutional Sparse Coding for Self-Supervised Hyperspectral Image Denoising (opens in a new tab)
- IGARSSIncremental Learning of Remote Sensing Target Classification with Class Hierarchy (opens in a new tab)
- ICMEIterative Refinement Network for Hyperspectral Image Denoising (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to ZhejiangFall 2027
Computer Science PhD (international applicants)
- Round
- Self-funded
- Opens
- —
- GRE
- See program page
- English
- Per ZJU language requirements
- Fee
- RMB 800
Not yet confirmed for this intake.
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