3 accepted papers
We propose a real-time visual-inertial dense SLAM system that utilizes the online data streams from back-to-back dual fisheye cameras setup, providing 360◦ coverage of the environment. Firstly, we employ a sliding-window-based front-end to estimate real-time poses from the binocular fisheye images a…
Risk item identification is vital for protecting the health of ecommerce trades. Existing solutions prefer to model structure information besides item attributes and optimize parameters in cross-entropy (CE) manners. However, the few labeled and imbalanced supervision in real-world scenarios usually…
Graph-level representation learning is to learn low-dimensional representation for the entire graph, which has shown a large impact on real-world applications. Recently, limited by expensive labeled data, contrastive learning based graph-level representation learning attracts considerable attention.…