3 citations · 6 across the 9 of their papers we have counts for
6 papers · 1 filter
Not All Tokens Need 40 Steps: Heterogeneous Step Allocation in Diffusion Transformers for Efficient Video Generation
Ernie Chu, Vishal M. Patel
Diffusion Transformers (DiTs) have achieved state-of-the-art video generation quality, but they incur immense computational cost because standard inference applies the same number…
Face-to-Face: A Video Dataset for Multi-Person Interaction Modeling
Ernie Chu, Vishal M. Patel
Modeling the reactive tempo of human conversation remains difficult because most audio-visual datasets portray isolated speakers delivering short monologues. We introduce \textbf{F…
Pixel Is Not a Barrier: An Effective Evasion Attack for Pixel-Domain Diffusion Models
Chun-Yen Shih, Li-Xuan Peng, Jia-Wei Liao +3
Diffusion Models have emerged as powerful generative models for high-quality image synthesis, with many subsequent image editing techniques based on them. However, the ease of text…
MeDM: Mediating Image Diffusion Models for Video-to-Video Translation with Temporal Correspondence Guidance
Ernie Chu, Tzuhsuan Huang, Shuo-Yen Lin +1
This study introduces an efficient and effective method, MeDM, that utilizes pre-trained image Diffusion Models for video-to-video translation with consistent temporal flow. The pr…
Diffusion to Confusion: Naturalistic Adversarial Patch Generation Based on Diffusion Model for Object Detector
Shuo-Yen Lin, Ernie Chu, Che-Hsien Lin +2
Many physical adversarial patch generation methods are widely proposed to protect personal privacy from malicious monitoring using object detectors. However, they usually fail to g…
Video ControlNet: Towards Temporally Consistent Synthetic-to-Real Video Translation Using Conditional Image Diffusion Models
Ernie Chu, Shuo-Yen Lin, Jun-Cheng Chen
In this study, we present an efficient and effective approach for achieving temporally consistent synthetic-to-real video translation in videos of varying lengths. Our method lever…