[CVPR 2021] Multi-Modal-CelebA: A Large-Scale Text-Driven Face Generation and Understanding Dataset
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Updated
Jun 1, 2024 - Python
[CVPR 2021] Multi-Modal-CelebA: A Large-Scale Text-Driven Face Generation and Understanding Dataset
[NeurIPS'23] "MagicBrush: A Manually Annotated Dataset for Instruction-Guided Image Editing".
[ICCV 2023] BoxDiff: Text-to-Image Synthesis with Training-Free Box-Constrained Diffusion
🔥 [ECCV 2022] TIPS: Text-Induced Pose Synthesis (official code).
[CVPR2024 Highlight] Official Code for "ImageNet-D: Benchmarking Neural Network Robustness on Diffusion Synthetic Object"
Official repository of OFA (ICML 2022). Paper: OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework
[CVPR '23] Unite and Conquer: Plug & Play Multi-Modal Synthesis using Diffusion Models
EasyNLP: A Comprehensive and Easy-to-use NLP Toolkit
[Journal of Artificial Intelligence Research] Source code for our paper "Exploiting Cultural Biases via Homoglyphs in Text-to-Image Synthesis".
The code for "Text-to-image synthesis with self-supervised learning"
The code for "Text-to-image synthesis with self-supervised bi-stage generative adversarial network"
Implementation of StackGANs for text-to-image generation in Tensorflow
PyTorch Implementation of Generative Adversarial Text to Image Synthesis
Modular image generation library
TISE: Bag of Metrics for Text-to-Image Synthesis Evaluation (ECCV 2022)
The pytorch implementation of the paper "text-guided neural image inpainting" at MM'2020 (oral)
✭ MAGNETRON ™ ✭: Implementation of Google's Dreambooth (with Stable Diffusion model) instead of IMAGEN (for making MAGNETRON ™ TECHNOLOGY IMAGINATION PROXIA). In particular this can be used to mimic the appearance of subjects in a given reference set and synthesize novel renditions of them in different contexts.
Official code of "StyleT2I: Toward Compositional and High-Fidelity Text-to-Image Synthesis" (CVPR 2022)
A CLI tool/python module for generating images from text using guided diffusion and CLIP from OpenAI.
(ICML-W, 2018) Text to image synthesis, by distilling concepts from multiple captions.
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