41 citations · 43 across the 5 of their papers we have counts for
5 papers
Self-supervised Geometric Features Discovery via Interpretable Attentio for Vehicle Re-Identification and Beyond (Complete Version)
Ming Li, Xinming Huang, Ziming Zhang
To learn distinguishable patterns, most of recent works in vehicle re-identification (ReID) struggled to redevelop official benchmarks to provide various supervisions, which requir…
RNN Training along Locally Optimal Trajectories via Frank-Wolfe Algorithm
Yun Yue, Ming Li, Venkatesh Saligrama +1
We propose a novel and efficient training method for RNNs by iteratively seeking a local minima on the loss surface within a small region, and leverage this directional vector for…
Self-supervised Geometric Features Discovery via Interpretable Attention for Vehicle Re-Identification and Beyond
Ming Li, Xinming Huang, Ziming Zhang
To learn distinguishable patterns, most of recent works in vehicle re-identification (ReID) struggled to redevelop official benchmarks to provide various supervisions, which requir…
LodoNet: A Deep Neural Network with 2D Keypoint Matchingfor 3D LiDAR Odometry Estimation
Ce Zheng, Yecheng Lyu, Ming Li +1
Deep learning based LiDAR odometry (LO) estimation attracts increasing research interests in the field of autonomous driving and robotics. Existing works feed consecutive LiDAR fra…
TreeRNN: Topology-Preserving Deep GraphEmbedding and Learning
Yecheng Lyu, Ming Li, Xinming Huang +3
General graphs are difficult for learning due to their irregular structures. Existing works employ message passing along graph edges to extract local patterns using customized grap…