Runnan Chen
- Rethinking Range View Representation for LiDAR Segmentation
2023/03/09 by Lingdong Kong, Kong, Lingdong, Youquan Liu +15 · 17 citations
Computer Science · Engineering · #Advanced Neural Network Applications #Autonomous Vehicle Technology and Safety #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Robotics (cs.RO) #Robotics and Sensor-Based Localization
- Robo3D: Towards Robust and Reliable 3D Perception against Corruptions
2023/03/30 by Lingdong Kong, Kong, Lingdong, Youquan Liu +15 · 17 citations
Computer Science · Medicine · #Advanced Neural Network Applications #COVID-19 diagnosis using AI #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Robotics (cs.RO)
- Towards Label-free Scene Understanding by Vision Foundation Models
2023/06/06 by Runnan Chen, Chen, Runnan, Youquan Liu +13 · 12 citations
Computer Science · #Advanced Image and Video Retrieval Techniques #Advanced Neural Network Applications #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Multimodal Machine Learning Applications
- LaVin-DiT: Large Vision Diffusion Transformer
2024/11/18 by Zhaoqing Wang, Xiaobo Xia, Wang, Zhaoqing +11 · 7 citations
Engineering · Physics and Astronomy · #CCD and CMOS Imaging Sensors #Advanced Optical Sensing Technologies
- Multi-Space Alignments Towards Universal LiDAR Segmentation
2024/05/02 by Youquan Liu, Liu, Youquan, Lingdong Kong +13 · 6 citations
Earth and Planetary Sciences · Engineering · Environmental Science · #3D Surveying and Cultural Heritage #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Remote Sensing and LiDAR Applications #Robotics (cs.RO) #Robotics and Sensor-Based Localization
- See More and Know More: Zero-shot Point Cloud Segmentation via Multi-modal Visual Data
2023/07/20 by Yuhang Lu, Lu, Yuhang, Qi Jiang +9 · 2 citations
Computer Science · Earth and Planetary Sciences · #3D Surveying and Cultural Heritage #Advanced Neural Network Applications #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences
- An Empirical Study of Training State-of-the-Art LiDAR Segmentation Models
2024/05/23 by Jiahao Sun, Chunmei Qing, Sun, Jiahao +23 · 2 citations
Environmental Science · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Remote Sensing and LiDAR Applications #Robotics (cs.RO)
- Zero-shot point cloud segmentation by transferring geometric primitives
2022/10/18 by Runnan Chen, Xinge Zhu, Chen, Runnan +11 · 1 citation
Computer Science · Earth and Planetary Sciences · Engineering · #3D Shape Modeling and Analysis #3D Surveying and Cultural Heritage #Advanced Neural Network Applications #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences
- Learning to Adapt SAM for Segmenting Cross-domain Point Clouds
2023/10/13 by Xidong Peng, Runnan Chen, Peng, Xidong +14 · 1 citation
Computer Science · #Advanced Neural Network Applications #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences
- UrbanGS: Semantic-Guided Gaussian Splatting for Urban Scene Reconstruction
2024/12/04 by Ziwen Li, Li, Ziwen, Jiaxin Huang +13 · 2 citations
Computer Science · Earth and Planetary Sciences · Environmental Science · #3D Surveying and Cultural Heritage #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Remote Sensing and LiDAR Applications #Video Surveillance and Tracking Methods
- Intern-GS: Vision Model Guided Sparse-View 3D Gaussian Splatting
2025/05/27 by Xiangyu Sun, Runnan Chen, Sun, Xiangyu +7 · 3 citations
Computer Science · Engineering · #Advanced Image and Video Retrieval Techniques #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Industrial Vision Systems and Defect Detection #Video Surveillance and Tracking Methods