5 citations · 7 across the 21 of their papers we have counts for
8 papers · 1 filter
LouvreSAE: Sparse Autoencoders for Interpretable and Controllable Style Transfer
Raina Panda, Daniel Fein, Arpita Singhal +3
Artistic style transfer in generative models remains a significant challenge, as existing methods often introduce style only via model fine-tuning, additional adapters, or prompt e…
Synthetic Human Action Video Data Generation with Pose Transfer
Vaclav Knapp, Matyas Bohacek
In video understanding tasks, particularly those involving human motion, synthetic data generation often suffers from uncanny features, diminishing its effectiveness for training.…
Can Pose Transfer Models Generate Realistic Human Motion?
Vaclav Knapp, Matyas Bohacek
Recent pose-transfer methods aim to generate temporally consistent and fully controllable videos of human action where the motion from a reference video is reenacted by a new ident…
GenAI Confessions: Black-box Membership Inference for Generative Image Models
Matyas Bohacek, Hany Farid
From a simple text prompt, generative-AI image models can create stunningly realistic and creative images bounded, it seems, by only our imagination. These models have achieved thi…
Human Action CLIPs: Detecting AI-generated Human Motion
Matyas Bohacek, Hany Farid
AI-generated video generation continues its journey through the uncanny valley to produce content that is increasingly perceptually indistinguishable from reality. To better protec…
The DeepSpeak Dataset
Sarah Barrington, Maty Bohacek, Hany Farid
Deepfakes represent a growing concern across domains such as disinformation, fraud, and non-consensual media. In particular, the rise of video conference and identity-driven attack…