Background Learnable Cascade for Zero-Shot Object Detection

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.

Generalized Zero-Shot Object Detection Object +3