WonwoongCho

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, ... 🧠

stablediffusion

High-Resolution Image Synthesis with Latent Diffusion Models

ControlNet

Let us control diffusion models!

LLaVA

[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.

Grounded-Segment-Anything

Grounded-SAM: Marrying Grounding-DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything

Awesome-Diffusion-Models

A collection of resources and papers on Diffusion Models

IF

GroundingDINO

Official implementation of the paper "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"

BLIP

PyTorch code for BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation

glide-text2im

GLIDE: a diffusion-based text-conditional image synthesis model

pytorch-fid

Compute FID scores with PyTorch.

textual_inversion

clip-interrogator

Image to prompt with BLIP and CLIP

sg2im

Code for "Image Generation from Scene Graphs", Johnson et al, CVPR 2018

Scene-Graph-Benchmark.pytorch

A new codebase for popular Scene Graph Generation methods (2020). Visualization & Scene Graph Extraction on custom images/datasets are provided. It's also a PyTorch implementation of paper “Unbiased Scene Graph Generation from Biased Training CVPR 2020”

graph-rcnn.pytorch

[ECCV 2018] Official code for "Graph R-CNN for Scene Graph Generation"

long_stable_diffusion

Long-form text-to-images generation, using a pipeline of deep generative models (GPT-3 and Stable Diffusion)

fastcomposer

FastComposer: Tuning-Free Multi-Subject Image Generation with Localized Attention

Compositional-Visual-Generation-with-Composable-Diffusion-Models-PyTorch

[ECCV 2022] Compositional Generation using Diffusion Models

OpenPSG

Benchmarking Panoptic Scene Graph Generation (PSG), ECCV'22

Mini-DALLE3

Mini-DALLE3: Interactive Text to Image by Prompting Large Language Models

EDICT

LayoutDiffusion

compose-visual-relations

[NeurIPS 2021 Spotlight] Learning to Compose Visual Relations

energy-based-scene-graph

Code release for Energy-Based Learning for Scene Graph Genertaion

SGDiff

Official implementation for "Diffusion-Based Scene Graph to Image Generation with Masked Contrastive Pre-Training" https://arxiv.org/abs/2211.11138

PENET

[CVPR 2023]Official Pytorch code for paper "Prototype-based Embedding Network for Scene Graph Generation"

EasyFace

Easy-to-use Face Analysis Tool

CanonicalSg2Im

Code for "Learning Canonical Representations for Scene Graph to Image Generation", Herzig & Bar et al., ECCV2020

SQUAT

The official code for Devil's on the Edges: Selective Quad Attention for Scene Graph Generation, CVPR2023.