1 code implementation • ICCV 2023 • Wenzhang Zhou, Heng Fan, Tiejian Luo, Libo Zhang
In this work, drawing inspiration from the concept of stability from the control theory that a robust system requires to remain consistent both externally and internally regardless of disturbances, we propose a novel framework that achieves unsupervised domain adaptive detection through stability analysis.
no code implementations • 1 Jan 2023 • Libo Zhang, Wenzhang Zhou, Heng Fan, Tiejian Luo, Haibin Ling
To reduce discrepancy in feature distributions between two domains, recent approaches achieve domain adaption through feature alignment in different granularities via adversarial learning.
1 code implementation • CVPR 2022 • Wenzhang Zhou, Dawei Du, Libo Zhang, Tiejian Luo, Yanjun Wu
Domain adaptive object detection is challenging due to distinctive data distribution between source domain and target domain.
no code implementations • 11 Dec 2019 • Wenzhang Zhou, Longyin Wen, Libo Zhang, Dawei Du, Tiejian Luo, Yanjun Wu
To reduce the impact of manually designed anchor boxes to adapt to different target motion patterns, we design the localization branch, which aims to coarsely localize the target to help the regression branch to generate accurate results.