😊 About Me
My name is Kaining Zhang, a Ph.D. student at Wuhan University. My research interests mainly lie in stereo vision and its applications (SLAM, Structure-from-Motion, large-scale visual localization, etc.). Previously I have been focused on loop closure detection to improve the performance of monocular SLAM (related fields: image retrieval, place recognition, image matching, etc.). Currently I am working on the intersection between 3D geometry and deep learning.
📖 Educations
- 2019.09 - 2024.06 (expected), Ph.D. student, Multi-Spectral Vision Processing Lab, Wuhan University, Wuhan, China.
- 2015.09 - 2019.06, B.S. in Electronic Information Science and Technology, Electronic Information School, Wuhan University, Wuhan, China.
📝 Publications
Loop Closure Detection via Bidirectional Manifold Representation Consensus
Kaining Zhang, Zizhuo Li, Jiayi Ma
IEEE Transactions on Intelligent Transportation Systems (TITS), 2022
- This is a comprehensive extension of our ICRA 2021. We speed up our algorithm by 63% and build the incremental database via HNSW. Meanwhile, experiments are conducted on more challenging datasets.
Appearance-Based Loop Closure Detection via Locality-Driven Accurate Motion Field Learning
Kaining Zhang, Xingyu Jiang, Jiayi Ma
IEEE Transactions on Intelligent Transportation Systems (TITS), 2021
- This is a more complete version of our IROS 2021. We propose a more reasonable loss to revise the motion field, and decrease the time complexity of the algorithm from O(N^3) to O(N). Meanwhile, experiments are conducted on more challenging datasets.
Appearance-based Loop Closure Detection via Bidirectional Manifold Representation Consensus
Kaining Zhang, Zizhuo Li, Jiayi Ma
IEEE International Conference on Robotics and Automation (ICRA), 2021
- We attempt to address loop closure detection (LCD) from the semantic aspect to the geometric one. Based on this idea, the proposed LCD system can achieve satisfying results.
Kaining Zhang, Xingyu Jiang, Xiaoguang Mei, Huabing Zhou, Jiayi Ma
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021
- We address feature matching in the perspective of motion field recovery, and add extra constraints to the motion field to make it more suitable for scenes within loop closure detection.
Loop Closure Detection with Reweighting NetVLAD and Local Motion and Structure Consensus
Kaining Zhang, Jiayi Ma, Junjun Jiang
IEEE/CAA Journal of Automatica Sinica (JAS), 2022
- We propose AttentionNetVLAD to extract more powerful image representation, and address feature matching via information lying on both a 2D space and an intrinsic manifold.
Loop Closure Detection via Locality Preserving Matching with Global Consensus
Jiayi Ma, Kaining Zhang, Junjun Jiang
IEEE/CAA Journal of Automatica Sinica (JAS), 2022
- A simple yet surprisingly effective feature matching approach is proposed for scenes within loop closure detection tasks (e.g., scenes with repetitive structures). The algorithm can provide reliable correspondences within only a few milliseconds.