dats77's starred repositories
Automold--Road-Augmentation-Library
This library augments road images to introduce various real world scenarios that pose challenges for training neural networks of Autonomous vehicles. Automold is created to train CNNs in specific weather and road conditions.
rain-rendering
Rain Rendering for Evaluating and Improving Robustness to Bad Weather (Tremblay et al., 2020) (S. S. Halder et al., 2019)
GaussianEditor
[CVPR 2024] GaussianEditor: Swift and Controllable 3D Editing with Gaussian Splatting
Deformable-3D-Gaussians
[CVPR 2024] Official implementation of "Deformable 3D Gaussians for High-Fidelity Monocular Dynamic Scene Reconstruction"
Deep-Learning-Interview-Book
深度学习面试宝典(含数学、机器学习、深度学习、计算机视觉、自然语言处理和SLAM等方向)
stable-diffusion-webui
Stable Diffusion web UI
EfficientSAM
EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything
AI-MTHRFCKR
An Awesome Collection of AI Resources, MTHRFCKR!
generative-models
Generative Models by Stability AI
stable-diffusion
A latent text-to-image diffusion model
annotated_deep_learning_paper_implementations
🧑🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
playground
A central hub for gathering and showcasing amazing projects that extend OpenMMLab with SAM and other exciting features.
tf-sr-attack
Official TensorFlow-based implementation of adversarial attack for super-resolution models
Point-UV-Diffusion
(ICCV2023) This is the official PyTorch implementation of ICCV2023 paper: Texture Generation on 3D Meshes with Point-UV Diffusion
active-iccv2023
Paper ACTIVE-ICCV2023
pytorch-grad-cam
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
deepmind-research
This repository contains implementations and illustrative code to accompany DeepMind publications