3 citations · 8 across the 6 of their papers we have counts for
6 papers
Thinking Outside the BBox: Unconstrained Generative Object Compositing
Gemma Canet Tarrés, Zhe Lin, Zhifei Zhang +6
Compositing an object into an image involves multiple non-trivial sub-tasks such as object placement and scaling, color/lighting harmonization, viewpoint/geometry adjustment, and s…
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…
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…
ALADIN-NST: Self-supervised disentangled representation learning of artistic style through Neural Style Transfer
Dan Ruta, Gemma Canet Tarres, Alexander Black +2
Representation learning aims to discover individual salient features of a domain in a compact and descriptive form that strongly identifies the unique characteristics of a given sa…
PARASOL: Parametric Style Control for Diffusion Image Synthesis
Gemma Canet Tarrés, Dan Ruta, Tu Bui +1
We propose PARASOL, a multi-modal synthesis model that enables disentangled, parametric control of the visual style of the image by jointly conditioning synthesis on both content a…
StyleBabel: Artistic Style Tagging and Captioning
Dan Ruta, Andrew Gilbert, Pranav Aggarwal +9
We present StyleBabel, a unique open access dataset of natural language captions and free-form tags describing the artistic style of over 135K digital artworks, collected via a nov…