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20232026
most citedDiffusion Model-Based Image Editing: A Survey

100 citations · 113 across the 20 of their papers we have counts for

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5 papers · 1 filter

cs.CV2024

Dual-Schedule Inversion: Training- and Tuning-Free Inversion for Real Image Editing

Jiancheng Huang, Yi Huang, Jianzhuang Liu +3

Text-conditional image editing is a practical AIGC task that has recently emerged with great commercial and academic value. For real image editing, most diffusion model-based metho…

physics.flu-dyn2024★ 2 cited

Pi-fusion: Physics-informed diffusion model for learning fluid dynamics

Jing Qiu, Jiancheng Huang, Xiangdong Zhang +4

Physics-informed deep learning has been developed as a novel paradigm for learning physical dynamics recently. While general physics-informed deep learning methods have shown early…

cs.CV2024★ 3 cited

Matten: Video Generation with Mamba-Attention

Yu Gao, Jiancheng Huang, Xiaopeng Sun +3

In this paper, we introduce Matten, a cutting-edge latent diffusion model with Mamba-Attention architecture for video generation. With minimal computational cost, Matten employs sp…

cs.CV2024★ 3 cited

NTIRE 2024 Challenge on Low Light Image Enhancement: Methods and Results

Xiaoning Liu, Zongwei Wu, Ao Li +109

This paper reviews the NTIRE 2024 low light image enhancement challenge, highlighting the proposed solutions and results. The aim of this challenge is to discover an effective netw…

cs.CV2024★ 100 cited

Diffusion Model-Based Image Editing: A Survey

Yi Huang, Jiancheng Huang, Yifan Liu +7

Denoising diffusion models have emerged as a powerful tool for various image generation and editing tasks, facilitating the synthesis of visual content in an unconditional or input…