61 citations · 63 across the 8 of their papers we have counts for
8 papers
ResEdit: Residual embeddings for precise generative image editing
Ahmet Canberk Baykal, Valentin Deschaintre, Yannick Hold-Geoffroy +4
Conditional diffusion image generators can be repurposed for editing through inversion, without the need for large-scale paired fine-tuning data. However, producing high-quality, t…
ReasonX: MLLM-Guided Intrinsic Image Decomposition
Alara Dirik, Tuanfeng Wang, Duygu Ceylan +2
Intrinsic image decomposition aims to separate images into physical components such as albedo, depth, normals, and illumination. While recent diffusion- and transformer-based model…
PRISM: A Unified Framework for Photorealistic Reconstruction and Intrinsic Scene Modeling
Alara Dirik, Tuanfeng Wang, Duygu Ceylan +2
We present PRISM, a unified framework that enables multiple image generation and editing tasks in a single foundational model. Starting from a pre-trained text-to-image diffusion m…
SuperGaussian: Repurposing Video Models for 3D Super Resolution
Yuan Shen, Duygu Ceylan, Paul Guerrero +4
We present a simple, modular, and generic method that upsamples coarse 3D models by adding geometric and appearance details. While generative 3D models now exist, they do not yet m…
VIVE3D: Viewpoint-Independent Video Editing using 3D-Aware GANs
Anna Frühstück, Nikolaos Sarafianos, Yuanlu Xu +2
We introduce VIVE3D, a novel approach that extends the capabilities of image-based 3D GANs to video editing and is able to represent the input video in an identity-preserving and t…
InsetGAN for Full-Body Image Generation
Anna Frühstück, Krishna Kumar Singh, Eli Shechtman +3
While GANs can produce photo-realistic images in ideal conditions for certain domains, the generation of full-body human images remains difficult due to the diversity of identities…
On the Robustness of Quality Measures for GANs
Motasem Alfarra, Juan C. Pérez, Anna Frühstück +3
This work evaluates the robustness of quality measures of generative models such as Inception Score (IS) and Fréchet Inception Distance (FID). Analogous to the vulnerability of dee…
TileGAN: Synthesis of Large-Scale Non-Homogeneous Textures
Anna Frühstück, Ibraheem Alhashim, Peter Wonka
We tackle the problem of texture synthesis in the setting where many input images are given and a large-scale output is required. We build on recent generative adversarial networks…