1 citations · 1 across the 8 of their papers we have counts for
6 papers · 1 filter
Anomaly-Preference Image Generation
Fuyun Wang, Yuanzhi Wang, Xu Guo +6
Synthesizing realistic and diverse anomalous samples from limited data is vital for robust model generalization. However, existing methods struggle to reconcile fidelity and divers…
Mixture Prototype Flow Matching for Open-Set Supervised Anomaly Detection
Fuyun Wang, Yuanzhi Wang, Xu Guo +6
Open-set supervised anomaly detection (OSAD) aims to identify unseen anomalies using limited anomalous supervision. However, existing prototype-based methods typically model normal…
Distribution Prototype Diffusion Learning for Open-set Supervised Anomaly Detection
Fuyun Wang, Tong Zhang, Yuanzhi Wang +4
In Open-set Supervised Anomaly Detection (OSAD), the existing methods typically generate pseudo anomalies to compensate for the scarcity of observed anomaly samples, while overlook…
Re-Attentional Controllable Video Diffusion Editing
Yuanzhi Wang, Yong Li, Mengyi Liu +4
Editing videos with textual guidance has garnered popularity due to its streamlined process which mandates users to solely edit the text prompt corresponding to the source video. R…
MPDS: A Movie Posters Dataset for Image Generation with Diffusion Model
Meng Xu, Tong Zhang, Fuyun Wang +3
Movie posters are vital for captivating audiences, conveying themes, and driving market competition in the film industry. While traditional designs are laborious, intelligent gener…
Big-model Driven Few-shot Continual Learning
Ziqi Gu, Chunyan Xu, Zihan Lu +3
Few-shot continual learning (FSCL) has attracted intensive attention and achieved some advances in recent years, but now it is difficult to again make a big stride in accuracy due…