Search Results for author: David Futschik

Found 7 papers, 2 papers with code

EVER: Exact Volumetric Ellipsoid Rendering for Real-time View Synthesis

no code implementations2 Oct 2024 Alexander Mai, Peter Hedman, George Kopanas, Dor Verbin, David Futschik, Qiangeng Xu, Falko Kuester, Jonathan T. Barron, yinda zhang

We present Exact Volumetric Ellipsoid Rendering (EVER), a method for real-time differentiable emission-only volume rendering.

StructuReiser: A Structure-preserving Video Stylization Method

no code implementations9 Sep 2024 Radim Spetlik, David Futschik, Daniel Sykora

We introduce StructuReiser, a novel video-to-video translation method that transforms input videos into stylized sequences using a set of user-provided keyframes.

SVG: 3D Stereoscopic Video Generation via Denoising Frame Matrix

no code implementations29 Jun 2024 Peng Dai, Feitong Tan, Qiangeng Xu, David Futschik, Ruofei Du, Sean Fanello, Xiaojuan Qi, yinda zhang

We propose a pose-free and training-free approach for generating 3D stereoscopic videos using an off-the-shelf monocular video generation model.

Denoising Video Generation +1

Controllable Light Diffusion for Portraits

no code implementations CVPR 2023 David Futschik, Kelvin Ritland, James Vecore, Sean Fanello, Sergio Orts-Escolano, Brian Curless, Daniel Sýkora, Rohit Pandey

We introduce light diffusion, a novel method to improve lighting in portraits, softening harsh shadows and specular highlights while preserving overall scene illumination.

Semantic Segmentation

STALP: Style Transfer with Auxiliary Limited Pairing

no code implementations20 Oct 2021 David Futschik, Michal Kučera, Michal Lukáč, Zhaowen Wang, Eli Shechtman, Daniel Sýkora

We present an approach to example-based stylization of images that uses a single pair of a source image and its stylized counterpart.

Style Transfer Translation

Real Image Inversion via Segments

1 code implementation12 Oct 2021 David Futschik, Michal Lukáč, Eli Shechtman, Daniel Sýkora

In this short report, we present a simple, yet effective approach to editing real images via generative adversarial networks (GAN).

Interactive Video Stylization Using Few-Shot Patch-Based Training

2 code implementations29 Apr 2020 Ondřej Texler, David Futschik, Michal Kučera, Ondřej Jamriška, Šárka Sochorová, Menglei Chai, Sergey Tulyakov, Daniel Sýkora

In this paper, we present a learning-based method to the keyframe-based video stylization that allows an artist to propagate the style from a few selected keyframes to the rest of the sequence.

Style Transfer Translation +1

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