collaborators

7 papers

cs.CV2025

SafetyPairs: Isolating Safety Critical Image Features with Counterfactual Image Generation

Alec Helbling, Shruti Palaskar, Kundan Krishna +3

What exactly makes a particular image unsafe? Systematically differentiating between benign and problematic images is a challenging problem, as subtle changes to an image, such as…

cs.CV2025

ComplicitSplat: Downstream Models are Vulnerable to Blackbox Attacks by 3D Gaussian Splat Camouflages

Matthew Hull, Haoyang Yang, Pratham Mehta +8

As 3D Gaussian Splatting (3DGS) gains rapid adoption in safety-critical tasks for efficient novel-view synthesis from static images, how might an adversary tamper images to cause h…

cs.CR2025

3D Gaussian Splat Vulnerabilities

Matthew Hull, Haoyang Yang, Pratham Mehta +8

With 3D Gaussian Splatting (3DGS) being increasingly used in safety-critical applications, how can an adversary manipulate the scene to cause harm? We introduce CLOAK, the first at…

cs.LG2024

RenderBender: A Survey on Adversarial Attacks Using Differentiable Rendering

Matthew Hull, Haoran Wang, Matthew Lau +8

Differentiable rendering techniques like Gaussian Splatting and Neural Radiance Fields have become powerful tools for generating high-fidelity models of 3D objects and scenes. Thei…

cs.HC2024

Interactive Visual Learning for Stable Diffusion

Seongmin Lee, Benjamin Hoover, Hendrik Strobelt +7

Diffusion-based generative models' impressive ability to create convincing images has garnered global attention. However, their complex internal structures and operations often pos…

cs.CV2024

ClickDiffusion: Harnessing LLMs for Interactive Precise Image Editing

Alec Helbling, Seongmin Lee, Polo Chau

Recently, researchers have proposed powerful systems for generating and manipulating images using natural language instructions. However, it is difficult to precisely specify many…

cs.AI2024

Point and Instruct: Enabling Precise Image Editing by Unifying Direct Manipulation and Text Instructions

Alec Helbling, Seongmin Lee, Polo Chau

Machine learning has enabled the development of powerful systems capable of editing images from natural language instructions. However, in many common scenarios it is difficult for…