2 citations · 7 across the 12 of their papers we have counts for
6 papers · 1 filter
CymbaDiff: Structured Spatial Diffusion for Sketch-based 3D Semantic Urban Scene Generation
Li Liang, Bo Miao, Xinyu Wang +3
Outdoor 3D semantic scene generation produces realistic and semantically rich environments for applications such as urban simulation and autonomous driving. However, advances in th…
On the Reliability of Vision-Language Models Under Adversarial Frequency-Domain Perturbations
Jordan Vice, Naveed Akhtar, Yansong Gao +2
Vision-Language Models (VLMs) are increasingly used as perceptual modules for visual content reasoning, including through captioning and DeepFake detection. In this work, we expose…
NatADiff: Adversarial Boundary Guidance for Natural Adversarial Diffusion
Max Collins, Jordan Vice, Tim French +1
Adversarial samples exploit irregularities in the manifold `learned' by deep learning models to cause misclassifications. The study of these adversarial samples provides insight in…
Exploring Bias in over 100 Text-to-Image Generative Models
Jordan Vice, Naveed Akhtar, Richard Hartley +1
We investigate bias trends in text-to-image generative models over time, focusing on the increasing availability of models through open platforms like Hugging Face. While these pla…
Image Watermarking of Generative Diffusion Models
Yunzhuo Chen, Jordan Vice, Naveed Akhtar +2
Embedding watermarks into the output of generative models is essential for establishing copyright and verifiable ownership over the generated content. Emerging diffusion model wate…
Skip Mamba Diffusion for Monocular 3D Semantic Scene Completion
Li Liang, Naveed Akhtar, Jordan Vice +2
3D semantic scene completion is critical for multiple downstream tasks in autonomous systems. It estimates missing geometric and semantic information in the acquired scene data. Du…