1 code implementation • CVPR 2018 • Omid Poursaeed, Isay Katsman, Bicheng Gao, Serge Belongie
In this paper, we propose novel generative models for creating adversarial examples, slightly perturbed images resembling natural images but maliciously crafted to fool pre-trained models.
no code implementations • 2 Jul 2018 • Isay Katsman, Rohun Tripathi, Andreas Veit, Serge Belongie
Semantic segmentation is a challenging vision problem that usually necessitates the collection of large amounts of finely annotated data, which is often quite expensive to obtain.
no code implementations • 20 Nov 2018 • Qian Huang, Zeqi Gu, Isay Katsman, Horace He, Pian Pawakapan, Zhiqiu Lin, Serge Belongie, Ser-Nam Lim
Neural networks are vulnerable to adversarial examples, malicious inputs crafted to fool trained models.
no code implementations • 4 Dec 2018 • Horace He, Aaron Lou, Qingxuan Jiang, Isay Katsman, Serge Belongie, Ser-Nam Lim
Research has shown that widely used deep neural networks are vulnerable to carefully crafted adversarial perturbations.
no code implementations • ICCV 2019 • Wei-Lin Hsiao, Isay Katsman, Chao-yuan Wu, Devi Parikh, Kristen Grauman
We introduce Fashion++, an approach that proposes minimal adjustments to a full-body clothing outfit that will have maximal impact on its fashionability.
2 code implementations • ICCV 2019 • Qian Huang, Isay Katsman, Horace He, Zeqi Gu, Serge Belongie, Ser-Nam Lim
We show that we can select a layer of the source model to perturb without any knowledge of the target models while achieving high transferability.
2 code implementations • ICML 2020 • Aaron Lou, Isay Katsman, Qingxuan Jiang, Serge Belongie, Ser-Nam Lim, Christopher De Sa
Recent advances in deep representation learning on Riemannian manifolds extend classical deep learning operations to better capture the geometry of the manifold.
3 code implementations • NeurIPS 2020 • Aaron Lou, Derek Lim, Isay Katsman, Leo Huang, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa
To better conform to data geometry, recent deep generative modelling techniques adapt Euclidean constructions to non-Euclidean spaces.
1 code implementation • NeurIPS 2021 • Isay Katsman, Aaron Lou, Derek Lim, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa
Tractably modelling distributions over manifolds has long been an important goal in the natural sciences.