1k citations · 3.1k across the 67 of their papers we have counts for
79 papers
DIFF-NST: Diffusion Interleaving For deFormable Neural Style Transfer
Dan Ruta, Gemma Canet Tarrés, Andrew Gilbert +3
Neural Style Transfer (NST) is the field of study applying neural techniques to modify the artistic appearance of a content image to match the style of a reference style image. Tra…
Realistic Saliency Guided Image Enhancement
S. Mahdi H. Miangoleh, Zoya Bylinskii, Eric Kee +2
Common editing operations performed by professional photographers include the cleanup operations: de-emphasizing distracting elements and enhancing subjects. These edits are challe…
SimpSON: Simplifying Photo Cleanup with Single-Click Distracting Object Segmentation Network
Chuong Huynh, Yuqian Zhou, Zhe Lin +4
In photo editing, it is common practice to remove visual distractions to improve the overall image quality and highlight the primary subject. However, manually selecting and removi…
NeAT: Neural Artistic Tracing for Beautiful Style Transfer
Dan Ruta, Andrew Gilbert, John Collomosse +2
Style transfer is the task of reproducing the semantic contents of a source image in the artistic style of a second target image. In this paper, we present NeAT, a new state-of-the…
Automatic High Resolution Wire Segmentation and Removal
Mang Tik Chiu, Xuaner Zhang, Zijun Wei +7
Wires and powerlines are common visual distractions that often undermine the aesthetics of photographs. The manual process of precisely segmenting and removing them is extremely te…
Ablating Concepts in Text-to-Image Diffusion Models
Nupur Kumari, Bingliang Zhang, Sheng-Yu Wang +3
Large-scale text-to-image diffusion models can generate high-fidelity images with powerful compositional ability. However, these models are typically trained on an enormous amount…