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)
- ECLIPSE: A Resource-Efficient Text-to-Image Prior for Image Generations
- InstanceDiffusion: Instance-level Control for Image Generation
- Instruct-Imagen: Image Generation with Multi-modal Instruction
- MACE: Mass Concept Erasure in Diffusion Models
- PAIR-Diffusion: Object-Level Image Editing with Structure-and-Appearance Paired Diffusion Models
- Residual Denoising Diffusion Models
- 2.图像编辑(Image Editing)
- PIA: Your Personalized Image Animator via Plug-and-Play Modules in Text-to-Image Models
- 3.视频生成(Video Generation/Image Synthesis)
- Seeing and Hearing: Open-domain Visual-Audio Generation with Diffusion Latent Aligners
- 4.视频编辑(Video Editing)
- 5.3D生成(3D Generation/3D 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
- 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)
- 2.图像编辑（Image Editing)
- 3.视频生成(Video Generation/Image Synthesis)
- 4.视频编辑(Video Editing)
- 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
)
