Liwei Ma
Papers
1
Total Citations
140
H-Index
1
About
Liwei Ma has made significant contributions to computer vision, with a primary focus on camera relocalization and deep learning. His most cited work, "Delving deeper into convolutional neural networks for camera relocalization" (2017, 140 citations), systematically investigates how CNNs can infer camera pose from a single monocular image, addressing key open problems in the field. Ma’s research explores architectural variations and training strategies to improve the accuracy and robustness of pose regression, advancing the practical deployment of visual localization systems. His work has been instrumental in bridging the gap between traditional geometric methods and modern learning-based approaches, enabling more reliable augmented reality and autonomous navigation applications. With over 140 citations on his leading paper alone, Ma’s contributions have influenced subsequent research in scene coordinate regression and end-to-end localization. His findings continue to guide researchers and engineers working on real-time camera tracking, demonstrating the enduring impact of his thoughtful analysis of CNN-based relocalization techniques.
Research Focus
Key Achievements
Top Papers
- 1Delving deeper into convolutional neural networks for camera relocalization140 citations · 2017