4 papers
ConsistentRFT: Reducing Visual Hallucinations in Flow-based Reinforcement Fine-Tuning
Xiaofeng Tan, Jun Liu, Yuanting Fan +7
Reinforcement Fine-Tuning (RFT) on flow-based models is crucial for preference alignment. However, they often introduce visual hallucinations like over-optimized details and semant…
Towards Fine-Grained Vision-Language Alignment for Few-Shot Anomaly Detection
Yuanting Fan, Jun Liu, Xiaochen Chen +5
Few-shot anomaly detection (FSAD) methods identify anomalous regions with few known normal samples. Most existing methods rely on the generalization ability of pre-trained vision-l…
Few-Shot Anomaly-Driven Generation for Anomaly Classification and Segmentation
Guan Gui, Bin-Bin Gao, Jun Liu +2
Anomaly detection is a practical and challenging task due to the scarcity of anomaly samples in industrial inspection. Some existing anomaly detection methods address this issue by…
EVE: Towards End-to-End Video Subtitle Extraction with Vision-Language Models
Haiyang Yu, Mengyang Zhao, Jinghui Lu +8
Video subtitles play a crucial role in short videos and movies, as they not only help models better understand video content but also support applications such as video translation…