9 citations · 11 across the 8 of their papers we have counts for
5 papers · 1 filter
AnomalyControl: Learning Cross-modal Semantic Features for Controllable Anomaly Synthesis
Shidan He, Lei Liu, Xiujun Shu +3
Anomaly synthesis is a crucial approach to augment abnormal data for advancing anomaly inspection. Based on the knowledge from the large-scale pre-training, existing text-to-image…
VidMan: Exploiting Implicit Dynamics from Video Diffusion Model for Effective Robot Manipulation
Youpeng Wen, Junfan Lin, Yi Zhu +4
Recent advancements utilizing large-scale video data for learning video generation models demonstrate significant potential in understanding complex physical dynamics. It suggests…
Predicting Genetic Mutation from Whole Slide Images via Biomedical-Linguistic Knowledge Enhanced Multi-label Classification
Gexin Huang, Chenfei Wu, Mingjie Li +6
Predicting genetic mutations from whole slide images is indispensable for cancer diagnosis. However, existing work training multiple binary classification models faces two challeng…
GrowCLIP: Data-aware Automatic Model Growing for Large-scale Contrastive Language-Image Pre-training
Xinchi Deng, Han Shi, Runhui Huang +7
Cross-modal pre-training has shown impressive performance on a wide range of downstream tasks, benefiting from massive image-text pairs collected from the Internet. In practice, on…
Continual Object Detection via Prototypical Task Correlation Guided Gating Mechanism
Binbin Yang, Xinchi Deng, Han Shi +6
Continual learning is a challenging real-world problem for constructing a mature AI system when data are provided in a streaming fashion. Despite recent progress in continual class…