Minimizing Maximum Model Discrepancy for Transferable Black-box Targeted Attacks

1 code implementation • CVPR 2023 • Anqi Zhao, Tong Chu, Yahao Liu, Wen Li, Jingjing Li, Lixin Duan

On the algorithmic side, we derive a new algorithm for black-box targeted attacks based on our theoretical analysis, in which we additionally minimize the maximum model discrepancy(M3D) of the substitute models when training the generator to generate adversarial examples.

Undoing the Damage of Label Shift for Cross-domain Semantic Segmentation

1 code implementation • CVPR 2022 • Yahao Liu, Jinhong Deng, Jiale Tao, Tong Chu, Lixin Duan, Wen Li

Existing works typically treat cross-domain semantic segmentation (CDSS) as a data distribution mismatch problem and focus on aligning the marginal distribution or conditional distribution.

Semantic Segmentation