77 citations · 80 across the 6 of their papers we have counts for
6 papers
Unsupervised Model Diagnosis
Yinong Oliver Wang, Eileen Li, Jinqi Luo +2
Ensuring model explainability and robustness is essential for reliable deployment of deep vision systems. Current methods for evaluating robustness rely on collecting and annotatin…
ControlNet++: Improving Conditional Controls with Efficient Consistency Feedback
Ming Li, Taojiannan Yang, Huafeng Kuang +4
To enhance the controllability of text-to-image diffusion models, existing efforts like ControlNet incorporated image-based conditional controls. In this paper, we reveal that exis…
LucidDreaming: Controllable Object-Centric 3D Generation
Zhaoning Wang, Ming Li, Chen Chen
With the recent development of generative models, Text-to-3D generations have also seen significant growth, opening a door for creating video-game 3D assets from a more general pub…
Zero-shot Model Diagnosis
Jinqi Luo, Zhaoning Wang, Chen Henry Wu +2
When it comes to deploying deep vision models, the behavior of these systems must be explicable to ensure confidence in their reliability and fairness. A common approach to evaluat…
Semantic Image Attack for Visual Model Diagnosis
Jinqi Luo, Zhaoning Wang, Chen Henry Wu +2
In practice, metric analysis on a specific train and test dataset does not guarantee reliable or fair ML models. This is partially due to the fact that obtaining a balanced, divers…
VOS: Learning What You Don't Know by Virtual Outlier Synthesis
Xuefeng Du, Zhaoning Wang, Mu Cai +1
Out-of-distribution (OOD) detection has received much attention lately due to its importance in the safe deployment of neural networks. One of the key challenges is that models lac…