Search Results for author:
Found 4 papers, 2 papers with code
Unsupervised Domain Adaptive Detection with Network Stability Analysis
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.
Robust Domain Adaptive Object Detection with Unified Multi-Granularity Alignment
To reduce discrepancy in feature distributions between two domains, recent approaches achieve domain adaption through feature alignment in different granularities via adversarial learning.
Multi-Granularity Alignment Domain Adaptation for Object Detection
Domain adaptive object detection is challenging due to distinctive data distribution between source domain and target domain.
SiamMan: Siamese Motion-aware Network for Visual Tracking
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.
