5 papers
Relighting as a Probe of Visual Priors via Augmented Latent Intrinsics
Xiaoyan Xing, Xiao Zhang, Sezer Karaoglu +2
Image-to-image relighting requires representations that separate illumination from scene properties while preserving dense geometry, material, and photometric cues. We use this tas…
Unblur-SLAM: Dense Neural SLAM for Blurry Inputs
Qi Zhang, Denis Rozumny, Francesco Girlanda +4
We propose Unblur-SLAM, a novel RGB SLAM pipeline for sharp 3D reconstruction from blurred image inputs. In contrast to previous work, our approach is able to handle different type…
Grab-3D: Detecting AI-Generated Videos from 3D Geometric Temporal Consistency
Wenhan Chen, Sezer Karaoglu, Theo Gevers
Recent advances in diffusion-based generation techniques enable AI models to produce highly realistic videos, heightening the need for reliable detection mechanisms. However, exist…
GaussianBlender: Instant Stylization of 3D Gaussians with Disentangled Latent Spaces
Melis Ocal, Xiaoyan Xing, Yue Li +3
3D stylization is central to game development, virtual reality, and digital arts, where the demand for diverse assets calls for scalable methods that support fast, high-fidelity ma…
LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting
Xiaoyan Xing, Konrad Groh, Sezer Karaoglu +2
We introduce LumiNet, a novel architecture that leverages generative models and latent intrinsic representations for effective lighting transfer. Given a source image and a target…