Depthsplat

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DepthSplat is an AI Agents & Automation tool that connects Gaussian splatting and depth estimation. It enables cross-task interactions for improved novel view synthesis and unsupervised depth pre-training.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Skill level

Technical

About

What is depthsplat?

DepthSplat is a research tool that connects Gaussian splatting and depth estimation, enabling cross-task interactions between these two computer vision techniques. It improves novel view synthesis with Gaussian splatting and facilitates unsupervised depth pre-training, leading to reduced depth prediction error. The tool provides pre-trained models hosted on Hugging Face, supports various datasets, and offers scripts for rendering videos and evaluating models. Developed using PyTorch, CUDA, and Python, DepthSplat allows for feed-forward reconstruction from multiple input views, demonstrating fast performance on GPUs. It is designed for researchers and developers in computer vision.

Best used for

Ideal for developers and data scientists who need to enhance 3D scene reconstruction, improve depth estimation accuracy, and generate novel views from limited input. Especially valuable for computer vision research and development in areas like 3D graphics and robotics.

Common actions

connect gaussian splatting

estimate depth

synthesize novel views

pre-train depth models

render videos

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Capabilities

Key features

Gaussian splatting connection
Depth estimation integration
Novel view synthesis
Unsupervised depth pre-training
Pre-trained models
Video rendering
Model evaluation

Target Audience

developerdata scientist

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What are the system requirements for running DepthSplat?

DepthSplat is developed using PyTorch 2.4.0, CUDA 12.4, and Python 3.10. It is recommended to set up a virtual environment using conda or venv before installation. While it can be trained on various GPUs, configurations like four RTX 4090s or a single A100 are verified to achieve similar results.

Where can I find pre-trained models for DepthSplat?

Pre-trained models for DepthSplat are hosted on Hugging Face. Detailed information about these models, including their specifications and usage, can be found in the MODEL_ZOO.md file within the project repository.

Can DepthSplat be used for depth prediction from multi-view images?

Yes, DepthSplat allows fine-tuning of its Gaussian Splatting pre-trained depth model using ground-truth depth supervision. The depth models are trained with a randomly selected number of input images (2 to 8) and can be used for depth prediction from multi-view posed images. Refer to scripts/inference_depth.sh for more details.

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