33 citations · 90 across the 17 of their papers we have counts for
4 papers · 1 filter
Understanding the Impact of Negative Prompts: When and How Do They Take Effect?
Yuanhao Ban, Ruochen Wang, Tianyi Zhou +3
The concept of negative prompts, emerging from conditional generation models like Stable Diffusion, allows users to specify what to exclude from the generated images.%, demonstrati…
The Crystal Ball Hypothesis in diffusion models: Anticipating object positions from initial noise
Yuanhao Ban, Ruochen Wang, Tianyi Zhou +3
Diffusion models have achieved remarkable success in text-to-image generation tasks; however, the role of initial noise has been rarely explored. In this study, we identify specifi…
MuLan: Multimodal-LLM Agent for Progressive and Interactive Multi-Object Diffusion
Sen Li, Ruochen Wang, Cho-Jui Hsieh +2
Existing text-to-image models still struggle to generate images of multiple objects, especially in handling their spatial positions, relative sizes, overlapping, and attribute bind…
Attacking by Aligning: Clean-Label Backdoor Attacks on Object Detection
Yize Cheng, Wenbin Hu, Minhao Cheng
Deep neural networks (DNNs) have shown unprecedented success in object detection tasks. However, it was also discovered that DNNs are vulnerable to multiple kinds of attacks, inclu…