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Domain-Adaptive Object Detection via Pseudo-Label Self-Training and Depth Priors
Unsupervised Domain Adaptation (UDA) for object detection remains challenging under adverse weather due to significant distribution shifts. While recent Vision Foundation Model (VFM) based methods show promise, they often encounter limitations in extreme domain gaps and pseudo-label noise. This paper proposes two enhan...