3D Vision Task

3D vision tasks aim to reconstruct and understand three-dimensional scenes from images or sensor data, enabling applications like robotics and augmented reality. Current research heavily utilizes transformer-based architectures, neural implicit functions, and state-space models to address challenges in tasks such as object pose estimation, scene reconstruction, and semantic understanding, often leveraging large-scale pre-trained models and datasets. These advancements are driving improvements in accuracy, efficiency, and robustness, particularly for handling complex scenes and diverse object types, thereby significantly impacting fields requiring accurate 3D scene perception.