44 citations · 71 across the 6 of their papers we have counts for
8 papers
EditFlow3D: Automated Local Editing of 3D Assets with Trajectory Preservation
Rui Nie, Chuang Wang, Haitao Zhou +4
Controllable local editing of 3D assets requires precise target localization and appropriate visual guidance. However, existing methods lack a simple yet accurate way to obtain 3D…
Fast Data Attribution for Text-to-Image Models
Sheng-Yu Wang, Aaron Hertzmann, Alexei A Efros +2
Data attribution for text-to-image models aims to identify the training images that most significantly influenced a generated output. Existing attribution methods involve considera…
Learning an Image Editing Model without Image Editing Pairs
Nupur Kumari, Sheng-Yu Wang, Nanxuan Zhao +7
Recent image editing models have achieved impressive results while following natural language editing instructions, but they rely on supervised fine-tuning with large datasets of i…
Identifying Prompted Artist Names from Generated Images
Grace Su, Sheng-Yu Wang, Aaron Hertzmann +3
A common and controversial use of text-to-image models is to generate pictures by explicitly naming artists, such as "in the style of Greg Rutkowski". We introduce a benchmark for…
SVGFusion: A VAE-Diffusion Transformer for Vector Graphic Generation
Ximing Xing, Juncheng Hu, Ziteng Xue +5
Generating high-quality Scalable Vector Graphics (SVGs) from text remains a significant challenge. Existing LLM-based models that generate SVG code as a flat token sequence struggl…
Sketch Your Own GAN
Sheng-Yu Wang, David Bau, Jun-Yan Zhu
Can a user create a deep generative model by sketching a single example? Traditionally, creating a GAN model has required the collection of a large-scale dataset of exemplars and s…
CNN-generated images are surprisingly easy to spot... for now
Sheng-Yu Wang, Oliver Wang, Richard Zhang +2
In this work we ask whether it is possible to create a "universal" detector for telling apart real images from these generated by a CNN, regardless of architecture or dataset used.…
Detecting Photoshopped Faces by Scripting Photoshop
Sheng-Yu Wang, Oliver Wang, Andrew Owens +2
Most malicious photo manipulations are created using standard image editing tools, such as Adobe Photoshop. We present a method for detecting one very popular Photoshop manipulatio…