Yong Liu
Professor
Works on robot intelligent perception and learning, including deep learning, SLAM and robot vision.
Yong Liu's lab at Zhejiang works on robot perception & SLAM and planning, control & multi-robot systems. 133 papers since 2023, 72 at top venues, mostly IROS and ICRA. 24 PhD students and 54 master's students. 80 alumni. Applications close .
At a glance
- papers, 2023–2026
- 35/ year
- at T1 venues
- 54%
- PhD students
- 24
- MS students
- 54
- alumni listed
- 80
Papers by yearfrom the lab homepage, 2023–2026
- 5 papers2026 · T1 0 · collecting
- 37 papers2025 · T1 24
- 46 papers2024 · T1 27
- 45 papers2023 · T1 21
T1 venuesOtherVenues: IROS, ICRA, CVPR, RA-L, TNNLS
Research focuspaper titles that use each topic's words
- Planning, control & multi-robot systems31 papers
- Robot perception & SLAM6 papers
- slam4 papers
- robot1 paper
- control science0 papers
Paper list
From the lab homepage.
20265 papers
- NeurocomputingAutomatic Data-Free Pruning via Channel Similarity Reconstruction (opens in a new tab)
- Advanced Engineering InformaticsKFS: KAN Based Adaptive Frequency Selection Learning Architecture for Long-term Time Series Forecasting (opens in a new tab)
- IEEE Transactions on Neural Networks and Learning SystemLeapVAD: A Leap in Autonomous Driving via Cognitive Perception and Dual-Process Thinking
- Pattern RecognitionMA-FSAR: Multimodal Adaptation of CLIP for Few-Shot Action Recognition (opens in a new tab)
- Neural NetworksWLR: Well-conditioned linear reconstruction for retraining-free pruning of LLMs (opens in a new tab)
202537 papers
- CVPR (T1)Action Detail Matters: Refining Video Recognition with Local Action Queries (opens in a new tab)
- TNNLS (T1)ActionCLIP: Adapting Language-Image Pretrained Models for Video Action Recognition (opens in a new tab)
- NeurIPS (T1)AdaVideoRAG: Omni-Contextual Adaptive Retrieval-Augmented Efficient Long Video Understanding
- TNNLS (T1)Adding before Pruning: Sparse Filter Fusion for Deep Convolutional Neural Networks via Auxiliary Attention (opens in a new tab)
- IEEE Transactions on Instrumentation and MeasurementAdversarial Multimodal Contrastive Learning for Robust Industrial Fault Diagnosis (opens in a new tab)
- ACM MMCogDDN: A Cognitive Demand-Driven Navigation with Decision Optimization and Dual-Process Thinking (opens in a new tab)
- TGRSDQFormer: Toward Unified LiDAR Panoptic Segmentation With Decoupled Queries for Large-Scale Outdoor Scenes (opens in a new tab)
- AAAI (T1)Driving in the Occupancy World: Vision-Centric 4D Occupancy Forecasting and Planning via World Models for Autonomous Driving (opens in a new tab)
- IROS (T1)Efficient Learning of A Unified Policy For Whole-body Manipulation and Locomotion Skills (opens in a new tab)
- RA-LEfficient Multi-Robot Task and Path Planning in Large-Scale Cluttered Environments (opens in a new tab)
- TPAMI (T1)EMOv2: Pushing 5M Vision Model Frontier (opens in a new tab)
- Computer Vision and Image UnderstandingExploring Plain ViT Features for Multi-class Unsupervised Visual Anomaly Detection (opens in a new tab)
202446 papers
- ICRA (T1)A Coarse-to-Fine Place Recognition Approach using Attention-guided Descriptors and Overlap Estimation (opens in a new tab)
- RA-LA Distributed Pipeline for Collaborative Pursuit in the Target Guarding Problem (opens in a new tab)
- AAAI (T1)A Multimodal, Multi-task Adapting Framework for Video Action Recognition (opens in a new tab)
- IROS (T1)A Robotic-centric Paradigm for 3D Human Tracking Under Complex Environments Using Multi-modal Adaptation (opens in a new tab)
- TPAMI (T1)AGDF-Net: Learning Domain Generalizable Depth Features with Adaptive Guidance Fusion (opens in a new tab)
- SensorsArtificial Intelligence in Pancreatic Image Analysis: A Review (opens in a new tab)
- ISASBeyond Traditional Driving Scenes: A Robotic-Centric Paradigm for 2D+3D Human Tracking Using Siamese Transformer Network (opens in a new tab)
- TIP (T1)Camera-Based 3D Semantic Scene Completion With Sparse Guidance Network (opens in a new tab)
- NeurIPS (T1)Continuously Learning, Adapting, and Improving: A Dual-Process Approach to Autonomous Driving
- TNNLS (T1)DCCD: Reducing Neural Network Redundancy via Distillation (opens in a new tab)
- ICASSP (T1)DCS: Debiased Contrastive Learning with Weak Supervision for Time Series Classification (opens in a new tab)
- IEEE Transactions on Industrial InformaticsDebiased Contrastive Learning for Time-Series Representation Learning and Fault Detection (opens in a new tab)
202345 papers
- ICRA (T1)A Unified BEV Model for Joint Learning 3D Local Features and Overlap Estimation (opens in a new tab)
- SensorsA USV-UAV Cooperative Trajectory Planning Algorithm with Hull Dynamic Constraints (opens in a new tab)
- TMMAdaptive Recurrent Forward Network for Dense Point Cloud Completion (opens in a new tab)
- AAMAS (T1)Adaptive Value Decomposition with Greedy Marginal Contribution Computation for Cooperative Multi-Agent Reinforcement Learning
- CVPR (T1)Better "CMOS" Produces Clearer Images: Learning Space-Variant Blur Estimation for Blind Image Super-Resolution (opens in a new tab)
- ICCV (T1)Boosting Few-Shot Action Recognition with Graph-Guided Hybrid Matching (opens in a new tab)
- ACM MMCenterLPS: Segment Instances by Centers for LiDAR Panoptic Segmentation (opens in a new tab)
- RA-LCoco-LIC: Continuous-Time Tightly-Coupled LiDAR-Inertial-Camera Odometry using Non-Uniform B-spline (opens in a new tab)
- IEEE/ASME Transactions on MechatronicsContinuous-Time Fixed-Lag Smoothing for LiDAR-Inertial-Camera SLAM (opens in a new tab)
- CVPRWCorrelation Pyramid Network for 3D Single Object Tracking (opens in a new tab)
- Pattern Analysis and ApplicationsCorrelation-based and content-enhanced network for video style transfer (opens in a new tab)
- Information SciencesDecomposing Shared Networks for Separate Cooperation with Multi-agent Reinforcement Learning (opens in a new tab)
Where alumni went80 listed
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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