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[ECCV2024] IDM-VTON : Improving Diffusion Models for Authentic Virtual Try-on in the Wild
InstantStyle: Free Lunch towards Style-Preserving in Text-to-Image Generation 🔥
Official implementation of MARS: Mixture of Auto-Regressive Models for Fine-grained Text-to-image Synthesis
Official implementations for paper: Zero-shot Image Editing with Reference Imitation
GLM-4 series: Open Multilingual Multimodal Chat LMs | 开源多语言多模态对话模型
Hunyuan-DiT : A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding
Lumina-T2X is a unified framework for Text to Any Modality Generation
add more control to fooocus
[TMLR 2024] Efficient Large Language Models: A Survey
Unofficial Implementation of Animate Anyone
A Collection of Papers and Codes for CVPR2024/ECCV2024 AIGC
MiniSora: A community aims to explore the implementation path and future development direction of Sora.
This project aim to reproduce Sora (Open AI T2V model), we wish the open source community contribute to this project.
AISystem 主要是指AI系统，包括AI芯片、AI编译器、AI推理和训练框架等AI全栈底层技术
深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系[email protected] 版权所有，违权必究 Tan 2018.06
Official release of InternLM2.5 7B base and chat models. 1M context support
A unified framework for 3D content generation.
GeoDream: Disentangling 2D and Geometric Priors for High-Fidelity and Consistent 3D Generation
🦜🔗 Build context-aware reasoning applications
Code release for NeRF (Neural Radiance Fields)
PyTorch implementation of InstructDiffusion, a unifying and generic framework for aligning computer vision tasks with human instructions.
VideoCrafter2: Overcoming Data Limitations for High-Quality Video Diffusion Models
PyTorch implementation for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
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.
General AI methods for Anything: AnyObject, AnyGeneration, AnyModel, AnyTask, AnyX