Depth Anything V2

Advanced Monocular Depth Estimation Model

CommonProductVideoDepth EstimationMonocular Vision

Depth Anything V2 is an improved monocular depth estimation model. Trained using synthetic images and a large amount of unlabeled real images, it provides more refined and robust depth predictions compared to the previous version. The model demonstrates significant improvements in both efficiency and accuracy, with a speed that is over 10 times faster than the latest Stable Diffusion-based models.

Provides more refined details compared to the previous version
More robust than Depth Anything V1 and SD-based models
Higher efficiency with a 10x speed improvement
Lightweight
with model sizes ranging from 25M to 1.3B parameters
Trains student models using large-scale pseudo-labeled real images
Established a general evaluation benchmark to support future research

Depth Anything V2 is suitable for fields requiring high-precision monocular depth estimation
such as autonomous driving
robot navigation
and augmented reality. Its strong generalization ability and high efficiency make it an ideal choice for these fields.

Obstacle detection and distance measurement in autonomous driving systems
Environmental perception and path planning in robot navigation
Achieving natural integration of virtual objects with the real world in augmented reality applications

1. Visit the official website of Depth Anything V2
2. Understand the basic information and technical parameters of the model
3. Download the pre-trained model or code and deploy it as needed
4. Prepare input image or video data
5. Use the model to perform depth estimation and obtain the depth map

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