3 accepted papers
Monocular depth estimation is essential for applications such as robotics. The complementary characteristics of event and image modalities have inspired fusion-based methods for robust depth estimation. However, existing methods rely on convolutional or attention-based architectures, which either ha
While significant progress has been achieved in multimodal facial generation using semantic masks and textual descriptions, conventional feature fusion approaches often fail to enable effective cross-modal interactions, thereby leading to suboptimal generation outcomes. To address this challenge, we
In this paper, we propose a new method called \textit{Self-Training with Dynamic Weighting} (STDW), which aims to enhance robustness in Gradual Domain Adaptation (GDA) by addressing the challenge of smooth knowledge migration from the source to the target domain. Traditional GDA methods mitigate dom…