# Zero-shot depth estimation

DepthPro is a foundational model for zero-shot metric monocular depth estimation, capable of generating high-resolution, high-precision depth maps.

A zero-shot monocular ranging depth estimation foundation model capable of synthesizing high-resolution depth maps with unparalleled sharpness and high-frequency details

Zero-shot monocular ranging depth estimation foundation model capable of synthesizing high-resolution depth maps with absolute scale prediction independent of camera intrinsics

This is a monocular depth estimation model based on the Apache-2.0 license, suitable for zero-shot depth estimation tasks in wild scenes.

Depth Anything is a depth estimation model based on the DPT architecture and DINOv2 backbone network, trained on approximately 62 million images, achieving state-of-the-art results in both relative and absolute depth estimation tasks.

Depth Anything is a depth estimation model based on the DPT architecture and DINOv2 backbone network, trained on approximately 62 million images, achieving state-of-the-art performance in zero-shot depth estimation.

Depth Anything is a depth estimation model based on the DPT architecture, utilizing the DINOv2 backbone network. It was trained on approximately 62 million images and excels in both relative and absolute depth estimation tasks.

A monocular image depth estimation model fine-tuned based on Stable Diffusion, featuring affine invariance for depth prediction in natural scenes

A monocular depth estimation model based on BEiT Transformer, capable of inferring fine depth information from a single image

A monocular depth estimation model based on Vision Transformer (ViT), trained on 1.4 million images, suitable for zero-shot depth prediction tasks.