Attention Based Depth

Attention-based depth estimation leverages depth information from various sources (e.g., RGB-D cameras, stereo vision) to improve the accuracy and robustness of computer vision tasks. Current research focuses on incorporating attention mechanisms into neural networks, such as graph attention networks and various attention-based depth nets, to selectively emphasize relevant features within depth maps and improve feature fusion from multiple sources (e.g., RGB and depth). This work is significant because accurate depth perception is crucial for applications like autonomous driving, 3D scene reconstruction, and object detection, particularly in challenging scenarios with camouflaged objects or textureless regions.