Apr 9, 2021 · An LBYL (`Look Before You Leap') Network is proposed for end-to-end trainable one-stage visual grounding. The idea behind LBYL-Net is intuitive ...

Thanks to the landmark feature convolution module, we mimic the human behavior of 'Look Before You Leap' to design an LBYL-Net, which takes full consideration ...

This repo implements paper Look Before You Leap: Learning Landmark Features For One-Stage Visual Grounding CVPR 2021. The core of this paper is Landmark ...

Thanks to the landmark feature convolution module, we mimic the human behavior of 'Look Before You Leap' to design an LBYL-Net, which takes full consideration ...

An LBYL ('Look Before You Leap') Network is proposed for end-to-end trainable one-stage visual grounding.

LPVA shows consistent improvements over the current one-stage methods [26] , [29]. Specifically, it achieves accuracies of 78.03% and 82.27% on both datasets, ...

Apr 9, 2021 · This work mimics the human behavior of 'Look Before You Leap' to design an LBYL-Net, which takes full consideration of contextual ...

Dec 31, 2021 · Look Before You. Leap: Learning Landmark Features for One-Stage Visual Ground- ing. In Proceedings of the IEEE/CVF Conference on Computer.

Feb 20, 2022 · The core of our LBYL-Net is a landmark feature convolution module that transmits the visual features with the guidance of linguistic description ...

This repo implements landmarkconv that aims to learn convolutional features outside the box. What's the difference? Box convolution. Standard conv has a ...