1 citations · 1 across the 4 of their papers we have counts for
4 papers
Exploring Few-Shot Defect Segmentation in General Industrial Scenarios with Metric Learning and Vision Foundation Models
Tongkun Liu, Bing Li, Xiao Jin +3
Industrial defect segmentation is critical for manufacturing quality control. Due to the scarcity of training defect samples, few-shot semantic segmentation (FSS) holds significant…
ChatDiT: A Training-Free Baseline for Task-Agnostic Free-Form Chatting with Diffusion Transformers
Lianghua Huang, Wei Wang, Zhi-Fan Wu +7
Recent research arXiv:2410.15027 arXiv:2410.23775 has highlighted the inherent in-context generation capabilities of pretrained diffusion transformers (DiTs), enabling them to seam…
IDEA-Bench: How Far are Generative Models from Professional Designing?
Chen Liang, Lianghua Huang, Jingwu Fang +7
Real-world design tasks - such as picture book creation, film storyboard development using character sets, photo retouching, visual effects, and font transfer - are highly diverse…
In-Context LoRA for Diffusion Transformers
Lianghua Huang, Wei Wang, Zhi-Fan Wu +6
Recent research arXiv:2410.15027 has explored the use of diffusion transformers (DiTs) for task-agnostic image generation by simply concatenating attention tokens across images. Ho…