1 code implementation • 12 Oct 2023 • Jinbo Song, Ruoran Huang, Xinyang Wang, Wei Huang, Qian Yu, Mingming Chen, Yafei Yao, Chaosheng Fan, Changping Peng, Zhangang Lin, Jinghe Hu, Jingping Shao
Industrial systems such as recommender systems and online advertising, have been widely equipped with multi-stage architectures, which are divided into several cascaded modules, including matching, pre-ranking, ranking and re-ranking.
no code implementations • 29 Apr 2022 • Xiaoxiao Xu, Zhiwei Fang, Qian Yu, Ruoran Huang, \\Chaosheng Fan, Yong Li, Yang He, Changping Peng, Zhangang Lin, Jingping Shao
The exposure sequence is being actively studied for user interest modeling in Click-Through Rate (CTR) prediction.
1 code implementation • 9 Oct 2020 • Ye Zheng, Ruoran Huang, Chuanqi Han, Xi Huang, Li Cui
The major contributions for BLC are as follows: (i) we propose a multi-stage cascade structure named Cascade Semantic R-CNN to progressively refine the alignment between visual and semantic of ZSD; (ii) we develop the semantic information flow structure and directly add it between each stage in Cascade Semantic RCNN to further improve the semantic feature learning; (iii) we propose the background learnable region proposal network (BLRPN) to learn an appropriate word vector for background class and use this learned vector in Cascade Semantic R CNN, this design makes \Background Learnable" and reduces the confusion between background and unseen classes.
Ranked #6 on Zero-Shot Object Detection on PASCAL VOC'07