1 code implementation • 7 Mar 2024 • Kaiwen Cai, Zhekai Duan, Gaowen Liu, Charles Fleming, Chris Xiaoxuan Lu
Recent advancements in Vision-Language (VL) models have sparked interest in their deployment on edge devices, yet challenges in handling diverse visual modalities, manual annotation, and computational constraints remain.
no code implementations • 15 Nov 2023 • Thomas Cilloni, Charles Fleming, Charles Walter
Our methodology involves observing the output of a stable diffusion model at different generative epochs and training a classification model to distinguish when a series of intermediates originated from a training sample or not.
no code implementations • 7 Nov 2022 • Chengkai Yu, Charles Fleming, Hai-Ning Liang
Video surveillance has become ubiquitous in the modern world.
no code implementations • 19 May 2022 • Thomas Cilloni, Charles Walter, Charles Fleming
Adversarial algorithms are optimization problems that minimize the accuracy of ML models by perturbing inputs, often using a model's loss function to craft such perturbations.
no code implementations • 20 Oct 2020 • Thomas Cilloni, Wei Wang, Charles Walter, Charles Fleming
In this paper we propose Ulixes, a strategy to generate visually non-invasive facial noise masks that yield adversarial examples, preventing the formation of identifiable user clusters in the embedding space of facial encoders.
no code implementations • 12 Apr 2016 • Michael S. Ryoo, Brandon Rothrock, Charles Fleming, Hyun Jong Yang
We introduce the paradigm of inverse super resolution (ISR), the concept of learning the optimal set of image transformations to generate multiple low-resolution (LR) training videos from a single video.