Depth Anything, a new MDE model jointly developed by HKU and TikTok, has brought breakthrough progress to the field of monocular depth estimation. This model can use massive unlabeled images for training, showing strong performance and practicality, and has excellent zero-sample capabilities. Its core lies in the design of an efficient data engine to automatically collect and label data, effectively solving the problem of large-scale data set construction and significantly reducing the generalization error of the model.
Depth Anything, a new MDE model jointly launched by HKU and TikTok, can utilize large-scale unlabeled images for monocular depth estimation. The model has strong performance and practicality, and provides better zero-sample capabilities. This model designs a data engine to collect and automatically label large-scale unlabeled data, expand the size of the data set, and reduce generalization errors. Its emergence brings new hope to the fields of robotics, autonomous driving and virtual reality.
The innovation of the Depth Anything model lies in its efficient data processing capabilities and excellent generalization performance, which provides a more accurate and reliable depth information perception solution for fields such as robotics, autonomous driving, and virtual reality. It has broad application prospects in the future. It is expected that follow-up research can further improve the accuracy and efficiency of the model and promote the rapid development of related fields.