3 citations · 4 across the 7 of their papers we have counts for
5 papers · 1 filter
High-Fidelity Document Stain Removal via A Large-Scale Real-World Dataset and A Memory-Augmented Transformer
Mingxian Li, Hao Sun, Yingtie Lei +5
Document images are often degraded by various stains, significantly impacting their readability and hindering downstream applications such as document digitization and analysis. Th…
CPSample: Classifier Protected Sampling for Guarding Training Data During Diffusion
Joshua Kazdan, Hao Sun, Jiaqi Han +2
Diffusion models have a tendency to exactly replicate their training data, especially when trained on small datasets. Most prior work has sought to mitigate this problem by imposin…
SpotActor: Training-Free Layout-Controlled Consistent Image Generation
Jiahao Wang, Caixia Yan, Weizhan Zhang +6
Text-to-image diffusion models significantly enhance the efficiency of artistic creation with high-fidelity image generation. However, in typical application scenarios like comic b…
Accelerating Non-Maximum Suppression: A Graph Theory Perspective
King-Siong Si, Lu Sun, Weizhan Zhang +4
Non-maximum suppression (NMS) is an indispensable post-processing step in object detection. With the continuous optimization of network models, NMS has become the ``last mile'' to…
OneActor: Consistent Character Generation via Cluster-Conditioned Guidance
Jiahao Wang, Caixia Yan, Haonan Lin +5
Text-to-image diffusion models benefit artists with high-quality image generation. Yet their stochastic nature hinders artists from creating consistent images of the same subject.…