Teach-DETR: Better Training DETR with Teachers

1 code implementation • 22 Nov 2022 • Linjiang Huang, Kaixin Lu, Guanglu Song, Liang Wang, Si Liu, Yu Liu, Hongsheng Li

In this paper, we present a novel training scheme, namely Teach-DETR, to learn better DETR-based detectors from versatile teacher detectors.

Spatial Transformation for Image Composition via Correspondence Learning

no code implementations • 6 Jul 2022 • Bo Zhang, Yue Liu, Kaixin Lu, Li Niu, Liqing Zhang

Instead, we propose a novel correspondence learning network (CorrelNet) to model the correspondence between foreground and background using cross-attention maps, based on which we can predict the target coordinate that each source coordinate of foreground should be mapped to on the background.

Virtual Try-on