Search Results for author:
Found 5 papers, 2 papers with code
Rethinking Artistic Copyright Infringements in the Era of Text-to-Image Generative Models
Recent text-to-image generative models such as Stable Diffusion are extremely adept at mimicking and generating copyrighted content, raising concerns amongst artists that their unique styles may be improperly copied.
Fast Adversarial Attacks on Language Models In One GPU Minute
Through human evaluations, we find that our untargeted attack causes Vicuna-7B-v1. 5 to produce ~15% more incorrect outputs when compared to LM outputs in the absence of our attack.
Invariant Learning via Diffusion Dreamed Distribution Shifts
Using the validation set, we evaluate several popular DNN image classifiers and find that the classification performance of models generally suffers on our background diverse images.
FOCUS: Familiar Objects in Common and Uncommon Settings
Standard training datasets for deep learning often contain objects in common settings (e. g., "a horse on grass" or "a ship in water") since they are usually collected by randomly scraping the web.
Unpaired Image Denoising
A majority of methods for image denoising are no exception to this rule and hence demand pairs of noisy and corresponding clean images.
Image and Video Processing
