Depth Representation

Depth representation in computer vision focuses on accurately estimating and representing the distance of objects from a camera, crucial for tasks like 3D scene reconstruction and object detection. Current research emphasizes improving depth map accuracy and generalization across diverse domains, employing techniques like self-supervised learning, transformer-based architectures (e.g., Deformable Transformers), and novel normalization strategies to enhance robustness and detail. These advancements are driving progress in applications such as autonomous driving, robotics, and augmented reality, where precise depth information is essential for reliable scene understanding and interaction.