CVPR2024｜AIGC(图像生成，视频生成等)相关论文汇总（附论文链接/开源代码/解析）【持续更新】

CVPR2024｜AIGC相关论文汇总（如果觉得有帮助，欢迎点赞和收藏）

• Awesome-CVPR2024-AIGC
• [1.图像生成(Image Generation/Image Synthesis)](#1.图像生成(Image Generation/Image Synthesis))
• • • [ECLIPSE: A Resource-Efficient Text-to-Image Prior for Image Generations](#ECLIPSE: A Resource-Efficient Text-to-Image Prior for Image Generations)
    • [InstanceDiffusion: Instance-level Control for Image Generation](#InstanceDiffusion: Instance-level Control for Image Generation)
    • [Instruct-Imagen: Image Generation with Multi-modal Instruction](#Instruct-Imagen: Image Generation with Multi-modal Instruction)
    • [MACE: Mass Concept Erasure in Diffusion Models](#MACE: Mass Concept Erasure in Diffusion Models)
    • [PAIR-Diffusion: Object-Level Image Editing with Structure-and-Appearance Paired Diffusion Models](#PAIR-Diffusion: Object-Level Image Editing with Structure-and-Appearance Paired Diffusion Models)
    • [Residual Denoising Diffusion Models](#Residual Denoising Diffusion Models)
• [2.图像编辑(Image Editing)](#2.图像编辑(Image Editing))
• • • [PIA: Your Personalized Image Animator via Plug-and-Play Modules in Text-to-Image Models](#PIA: Your Personalized Image Animator via Plug-and-Play Modules in Text-to-Image Models)
• [3.视频生成(Video Generation/Image Synthesis)](#3.视频生成(Video Generation/Image Synthesis))
• • • [Seeing and Hearing: Open-domain Visual-Audio Generation with Diffusion Latent Aligners](#Seeing and Hearing: Open-domain Visual-Audio Generation with Diffusion Latent Aligners)
• [4.视频编辑(Video Editing)](#4.视频编辑(Video Editing))
• [5.3D生成(3D Generation/3D Synthesis)](#5.3D生成(3D Generation/3D Synthesis))
• • • [EscherNet: A Generative Model for Scalable View Synthesis](#EscherNet: A Generative Model for Scalable View Synthesis)
• 6.其他多任务(Others)
• • • [InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks](#InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks)
    • [Q-Instruct: Improving Low-level Visual Abilities for Multi-modality Foundation Models](#Q-Instruct: Improving Low-level Visual Abilities for Multi-modality Foundation Models)
• 参考
• 相关整理

Awesome-CVPR2024-AIGC

A Collection of Papers and Codes for CVPR2024 AIGC

整理汇总下今年CVPR AIGC相关的论文和代码，具体如下。

欢迎star，fork和PR~
优先在Github更新 ：Awesome-CVPR2024-AIGC，欢迎star~
知乎 ：https://zhuanlan.zhihu.com/p/684325134

参考或转载请注明出处

CVPR2024官网：https://cvpr.thecvf.com/Conferences/2024

CVPR完整论文列表：

开会时间：2024年6月17日-6月21日

论文接收公布时间：

【Contents】

• [1.图像生成(Image Generation/Image Synthesis)](#1.图像生成(Image Generation/Image Synthesis))
• [2.图像编辑（Image Editing)](#2.图像编辑（Image Editing))
• [3.视频生成(Video Generation/Image Synthesis)](#3.视频生成(Video Generation/Image Synthesis))
• [4.视频编辑(Video Editing)](#4.视频编辑(Video Editing))
• [5.3D生成(3D Generation/3D Synthesis)](#5.3D生成(3D Generation/3D Synthesis))
• 6.其他多任务(Others)

1.图像生成(Image Generation/Image Synthesis)

ECLIPSE: A Resource-Efficient Text-to-Image Prior for Image Generations

• Paper: https://arxiv.org/abs/2312.04655
• Code: https://github.com/eclipse-t2i/eclipse-inference

InstanceDiffusion: Instance-level Control for Image Generation

• Paper: https://arxiv.org/abs/2402.03290
• Code: https://github.com/frank-xwang/InstanceDiffusion

Instruct-Imagen: Image Generation with Multi-modal Instruction

• Paper: https://arxiv.org/abs/2401.01952

MACE: Mass Concept Erasure in Diffusion Models

• Paper:
• Code: https://github.com/Shilin-LU/MACE

PAIR-Diffusion: Object-Level Image Editing with Structure-and-Appearance Paired Diffusion Models

• Paper: https://arxiv.org/abs/2303.17546
• Code: https://github.com/Picsart-AI-Research/PAIR-Diffusion

Residual Denoising Diffusion Models

• Paper: https://arxiv.org/abs/2308.13712
• Code: https://github.com/nachifur/RDDM

2.图像编辑(Image Editing)

PIA: Your Personalized Image Animator via Plug-and-Play Modules in Text-to-Image Models

• Paper: https://arxiv.org/abs/2312.13964
• Code: https://github.com/open-mmlab/PIA

3.视频生成(Video Generation/Image Synthesis)

Seeing and Hearing: Open-domain Visual-Audio Generation with Diffusion Latent Aligners

• Paper: https://arxiv.org/abs/2308.13712
• Code: https://github.com/yzxing87/Seeing-and-Hearing

4.视频编辑(Video Editing)

5.3D生成(3D Generation/3D Synthesis)

EscherNet: A Generative Model for Scalable View Synthesis

• Paper: https://arxiv.org/abs/2402.03908
• Code: https://github.com/kxhit/EscherNet

6.其他多任务(Others)

InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks

• Paper: https://arxiv.org/abs/2312.14238
• Code: https://github.com/OpenGVLab/InternVL

Q-Instruct: Improving Low-level Visual Abilities for Multi-modality Foundation Models

• Paper: https://arxiv.org/abs/2311.06783
• Code: https://github.com/Q-Future/Q-Instruct
  持续更新~

参考

CVPR 2024 论文和开源项目合集(Papers with Code)

相关整理

• Awesome-AIGC-Research-Groups
• Awesome-Low-Level-Vision-Research-Groups
• Awesome-CVPR2024-CVPR2021-CVPR2020-Low-Level-Vision
• Awesome-ECCV2020-Low-Level-Vision