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cs.CV2026

Geometric Image Editing via Effects-Sensitive In-Context Inpainting with Diffusion Transformers

Shuo Zhang, Wenzhuo Wu, Huayu Zhang +8

Recent advances in diffusion models have significantly improved image editing. However, challenges persist in handling geometric transformations, such as translation, rotation, and…

cs.CV2025

Anti-Aesthetics: Protecting Facial Privacy against Customized Text-to-Image Synthesis

Songping Wang, Yueming Lyu, Shiqi Liu +4

The rise of customized diffusion models has spurred a boom in personalized visual content creation, but also poses risks of malicious misuse, severely threatening personal privacy…

cs.CV2024

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…

cs.CV2024

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…

cs.CV2024

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.…

cs.CV2024

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…