Temporal Stereo

Temporal stereo leverages the temporal consistency of video data to improve depth estimation and 3D scene understanding, addressing the inherent ambiguities of traditional stereo vision. Current research focuses on developing efficient algorithms, often incorporating cost volume methods and neural networks, to fuse information across multiple frames and views, particularly within the context of autonomous driving and surgical instrument segmentation. These advancements enhance the accuracy and robustness of 3D object detection and scene reconstruction in challenging scenarios, impacting fields like robotics, autonomous vehicles, and medical imaging.