# Depth Anything V2

Canonical page: https://fuser.studio/models/depth-anything-v2

Depth Anything V2 in Fuser turns any image into a relative depth map. Feed it to ControlNet or 3D nodes to keep the scene's spatial layout in new renders.

## Specs

| Spec | Value |
| --- | --- |
| Inputs | Image |
| Output | image |
| Cost | 7 credits per run |

Extract clean relative depth maps with luminous foreground contours and smooth spatial gradients for ControlNet conditioning

Creator: ByteDance

[Extract Depth Map](https://app.fuser.studio)

## How Depth Anything V2 works

Convert standard 2D photographs into high-contrast relative depth maps in three simple steps to prepare visual assets for structural generative workflows.

### Upload source image

Select a high-resolution photograph with distinct perspective cues and foreground separation.

### Extract relative depth

Process the image through transformer-based monocular estimation to map spatial proximity.

### Export for ControlNet

Use the generated grayscale depth map to drive Stable Diffusion workflows or 3D mesh displacement.

## What Depth Anything V2 is good at

Engineered with massive synthetic-to-real distillation, delivering precise edge separation, smooth spatial gradients, and rapid monocular depth estimation.

### Sharp Boundary Delineation

Isolates foreground subjects from complex backgrounds with luminous white proximity values and clean silhouette contours, preventing edge bleed in ControlNet passes.

### Continuous Spatial Gradients

Maps smooth, progressive depth transitions across complex surfaces, rendering subtle curvature and receding planes without severe stepped banding.

### Zero-Shot Geometry Extraction

Estimates reliable relative depth from uncalibrated 2D scenes using synthetic-data pretraining, unlocking instant layout guides for multi-room interiors and facades.

### Sub-Second Monocular Inference

Delivers instant depth maps over ten times faster than diffusion-based estimators, keeping real-time Stable Diffusion and generation pipelines frictionless.

## Made with Depth Anything V2

Explore grayscale relative depth outputs across varied subjects, highlighting boundary definition and spatial separation from foreground to background.

### High-contrast cinematic framing with clear subject-to-void separation

### Industrial artisan study with distinct mid-ground planes

### Minimalist graphic poster with bold planar depth

### E-commerce product still highlighting tactile materials

## What people build with Depth Anything V2

Discover how creators, VFX artists, and designers integrate relative depth maps into ControlNet conditioning, 3D displacement, and compositing pipelines.

### Fashion Lookbook Conditioning

Preserve exact garment silhouettes and model poses when generating seasonal lookbook variations through Stable Diffusion ControlNet pipelines.

### Architectural Massing and Layout

Translate conceptual building sketches and reference photos into structured spatial guides for iterative architectural rendering.

### 3D Mesh Displacement

Convert 2D product imagery into clean displacement maps to rapidly prototype 3D models and bas-relief geometry.

### Background Segmentation and Compositing

Generate sharp luminance-based separation masks to isolate hero subjects from backgrounds for commercial VFX and graphic asset pipelines.

### Scene Depth for VFX Matte Painting

Extract instant spatial maps from live-action plates to guide depth-of-field effects, volumetric fog insertion, and set extensions.

## Frequently Asked Questions

### What makes Depth Anything V2 better than the original version?

Depth Anything V2 produces substantially sharper object boundaries and cleaner depth gradients by replacing noisy real-world training labels with high-precision synthetic datasets (~595K images) and scaling teacher-student distillation across 62+ million images. This eliminates common spatial distortions and edge bleed.

### What is Depth Anything V2 best used for?

Depth Anything V2 is optimized for ControlNet depth guidance in Stable Diffusion and SDXL pipelines, 3D mesh displacement mapping from 2D images, and foreground-background separation. Its sub-second execution makes it ideal for real-time generative workflows.

### How fast is Depth Anything V2 compared to diffusion-based depth models?

It is over 10x faster and significantly more lightweight than diffusion-based monocular depth estimators such as Marigold. Depth Anything V2 runs in sub-second inference times on single images, making it practical for batch preprocessing and interactive creative workflows.

### What inputs and outputs does Depth Anything V2 support?

Depth Anything V2 accepts standard 2D image inputs and outputs a single relative grayscale depth map where luminance represents proximity, with near objects rendered in bright white and distant elements receding into black.

### When should I avoid using Depth Anything V2?

Avoid using Depth Anything V2 for high-precision 3D metrology or robotics requiring exact metric millimeter measurements, as it estimates relative rather than absolute depth. It is also not recommended for raw frame-by-frame video without temporal smoothing, or scenes dominated by ultra-thin rigging, hair, or transparent glass reflections.

### Who created Depth Anything V2 and when was it released?

Depth Anything V2 was created by researchers at ByteDance and released on June 13, 2024, subsequently presented at NeurIPS 2024.

## Try Depth Anything V2 on Fuser

Extract clean relative depth maps with luminous foreground contours and smooth spatial gradients for ControlNet conditioning

[Extract Depth Map](https://app.fuser.studio)

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- [Gemini Image](https://fuser.studio/models/gemini-image.md)
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Node reference: [Depth Anything V2 docs](https://docs.fuser.studio/docs/nodes/image/depth-anything-v2.md)

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- [AI Image Generation Glossary: 31 Terms Explained](https://fuser.studio/articles/ai-image-generation-glossary.md)