Popular GitHub Repositories for Depth Superresolution

In-depth tutorials on LLMs, RAGs and real-world AI agent applications.

Effortless data labeling with AI support from Segment Anything and other awesome models.

An in-depth machine learning tutorial introducing readers to a whole machine learning pipeline from scratch.

papers about Face Detection; Face Alignment; Face Recognition && Face Identification && Face Verification && Face Representation; Face Reconstruction; Face Tracking; Face Super-Resolution && Face Deblurring; Face Generation && Face Synthesis; Face Transfer; Face Anti-Spoofing; Face Retrieval;

[ICCV 2019] Monocular depth estimation from a single image

A curated list of the latest breakthroughs in AI (in 2022) by release date with a clear video explanation, link to a more in-depth article, and code.

A procedural Blender pipeline for photorealistic training image generation

A curated list of the latest breakthroughs in AI (in 2021) by release date with a clear video explanation, link to a more in-depth article, and code.

[CVPR 2024 - Oral, Best Paper Award Candidate] Marigold: Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation

Metric depth estimation from a single image

Automated Deep Learning: Neural Architecture Search Is Not the End (a curated list of AutoDL resources and an in-depth analysis)

A curated list of the latest breakthroughs in AI by release date with a clear video explanation, link to a more in-depth article, and?code

An unsupervised learning framework for depth and ego-motion estimation from monocular videos

High Resolution Depth Maps for Stable Diffusion WebUI

High Quality Monocular Depth Estimation via Transfer Learning

In-depth tutorials for implementing deep learning models on your own with PyTorch.

Depth map library for use with the Control Net extension for Automatic1111/stable-diffusion-webui

[ECCV 2022] SimpleRecon: 3D Reconstruction Without 3D Convolutions

[TPAMI'23] Unifying Flow, Stereo and Depth Estimation

Deeper Depth Prediction with Fully Convolutional Residual Networks (FCRN)