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

Visit

Depth Anything V2 Visit Over Time

Monthly Visits

10100

Bounce Rate

59.08%

Page per Visit

1.1

Visit Duration

00:00:12

Depth Anything V2 Visit Trend

Depth Anything V2 Visit Geography

Depth Anything V2 Traffic Sources

Depth Anything V2 Alternatives

Flux.1 Lite — An 8B parameter variational autoencoder model designed for efficient text-to-image generation.

Image•Text-to-image•AI generation

108

Long-LRM — Efficient 3D Gaussian reconstruction model for fast large-scale scene regeneration

Image•3D Reconstruction•Gaussian Model

108

Open Source Computer Vision Library — Open Source Computer Vision Library

Productivity•Computer Vision•Machine Learning

Pixtral 12B — The first multimodal Mistral model, supporting hybrid task processing for images and text.

Productivity•Multimodal•AI Model

Shangchen Zhou — A blog website focused on research and innovation in the fields of computer vision and machine learning.

OpenSource•Computer Vision•Machine Learning

pixtral-12b-240910 — A multimodal large language model that supports understanding of both images and text.

Image•Multimodal•Image Processing

120

bonding_w_geimini — A Streamlit application utilizing the Gemini API for image object detection.

Image•Image Processing•Object Detection

LabelU — An open-source data labeling tool that enhances machine learning model performance.

Productivity•Data Annotation•Machine Learning

378

Florence-2-large-ft — An advanced vision foundation model that supports a variety of visual and vision-language tasks.

Image•Image Processing•Natural Language Processing

330

MistoLine — A multifunctional and powerful SDXL-ControlNet model designed for the adjustment of various line arts.

Image•Image Processing•Line Art

792

IC-Light — IC-Light is a project for image lighting manipulation.

Image•Image Processing•Machine Learning

1800

IntrinsicAnything — A cutting-edge inverse rendering learning diffusion prior method that recovers object materials from any image and achieves single-view image relighting.

Image•Inverse Rendering•Material Recovery

498

InstantMesh — High-efficiency 3D mesh generation framework

Image•3D Modeling•Image Processing

3366

Nightshade — A tool that transforms images into 'poison' samples that are not suitable for training machine learning models.

Image•Copyright Protection•Machine Learning

294

SDXS — Real-time, one-step latent diffusion model, allowing for image-condition controlled generation.

Image•Artificial Intelligence•Machine Learning

4266

MATLAB — MATLAB is the simplest and most effective software environment for engineers and scientists.

Programming•Engineers•Scientists

168

OpenCV — Real-time optimized computer vision library

Image•Computer vision•Image processing

246

Lingyun Open Platform — Open Platform

ChineseSelection•Development Programming•AI Open Platform

354

Control-LoRA — Model control technique based on low-rank parameter optimization

Image•Image Processing•Model Control

330

Dpt Depth — Dpt Depth Estimation + 3D

Image•Depth Estimation•3D

1380

GPU Finder — GPU Finder is a platform that helps customers discover GPU instances available from global public cloud vendors. Through GPU Finder, users can quickly find and compare GPU instances offered by major cloud providers, including their prices, configurations, and performance. This allows users to choose the GPU instance that best meets their needs. Whether conducting machine learning, deep learning, image processing, or scientific computing, GPU Finder can help users find the right GPU instance quickly. The platform offers rich filtering and sorting capabilities, allowing users to precisely screen according to their requirements, thereby saving time and cost. Both beginners and experienced developers can easily use GPU Finder to discover and rent suitable GPU instances.

Productivity•GPU Finder•GPU Instances

Kalavai — AI cloud platform serving everyone

Programming•Cloud Computing•Development Platform

Neural Magic — Experts in AI model deployment and inference optimization

InternationalSelection•Machine Learning•Model Optimization

Qwen2.5-Coder-0.5B — The 0.5B parameter code generation model in the Qwen2.5-Coder series.

Programming•Code Generation•Code Reasoning

face_anon_simple — Facial anonymization technology that retains key details while effectively protecting privacy.

Image•Facial Anonymization•Privacy Protection

Best AI Websites & Tools