2 citations · 2 across the 4 of their papers we have counts for
4 papers
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…
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…
Bootstrap Diffusion Model Curve Estimation for High Resolution Low-Light Image Enhancement
Jiancheng Huang, Yifan Liu, Shifeng Chen
Learning-based methods have attracted a lot of research attention and led to significant improvements in low-light image enhancement. However, most of them still suffer from two ma…
Graph Edit Distance Learning via Different Attention
Jiaxi Lv, Liang Zhang, Yi Huang +2
Recently, more and more research has focused on using Graph Neural Networks (GNN) to solve the Graph Similarity Computation problem (GSC), i.e., computing the Graph Edit Distance (…