Search Results for author: Ivan Skorokhodov

Found 25 papers, 12 papers with code

Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors

1 code implementation30 Jun 2023 Guocheng Qian, Jinjie Mai, Abdullah Hamdi, Jian Ren, Aliaksandr Siarohin, Bing Li, Hsin-Ying Lee, Ivan Skorokhodov, Peter Wonka, Sergey Tulyakov, Bernard Ghanem

We present Magic123, a two-stage coarse-to-fine approach for high-quality, textured 3D meshes generation from a single unposed image in the wild using both2D and 3D priors.

Image to 3D

StyleGAN-V: A Continuous Video Generator with the Price, Image Quality and Perks of StyleGAN2

1 code implementation CVPR 2022 Ivan Skorokhodov, Sergey Tulyakov, Mohamed Elhoseiny

We build our model on top of StyleGAN2 and it is just ${\approx}5\%$ more expensive to train at the same resolution while achieving almost the same image quality.

Video Generation

PET-NeuS: Positional Encoding Tri-Planes for Neural Surfaces

1 code implementation CVPR 2023 Yiqun Wang, Ivan Skorokhodov, Peter Wonka

The first component is to borrow the tri-plane representation from EG3D and represent signed distance fields as a mixture of tri-planes and MLPs instead of representing it with MLPs only.

Surface Reconstruction

HF-NeuS: Improved Surface Reconstruction Using High-Frequency Details

1 code implementation15 Jun 2022 Yiqun Wang, Ivan Skorokhodov, Peter Wonka

We develop HF-NeuS, a novel method to improve the quality of surface reconstruction in neural rendering.

Neural Rendering Surface Reconstruction +1

EpiGRAF: Rethinking training of 3D GANs

1 code implementation21 Jun 2022 Ivan Skorokhodov, Sergey Tulyakov, Yiqun Wang, Peter Wonka

In this work, we show that it is possible to obtain a high-resolution 3D generator with SotA image quality by following a completely different route of simply training the model patch-wise.

3D-Aware Image Synthesis

Loss Landscape Sightseeing with Multi-Point Optimization

1 code implementation9 Oct 2019 Ivan Skorokhodov, Mikhail Burtsev

We present multi-point optimization: an optimization technique that allows to train several models simultaneously without the need to keep the parameters of each one individually.

Class Normalization for (Continual)? Generalized Zero-Shot Learning

3 code implementations19 Jun 2020 Ivan Skorokhodov, Mohamed Elhoseiny

Normalization techniques have proved to be a crucial ingredient of successful training in a traditional supervised learning regime.

Generalized Zero-Shot Learning

Interpolating Points on a Non-Uniform Grid using a Mixture of Gaussians

1 code implementation24 Dec 2020 Ivan Skorokhodov

In this work, we propose an approach to perform non-uniform image interpolation based on a Gaussian Mixture Model.

Continual Zero-Shot Learning through Semantically Guided Generative Random Walks

1 code implementation ICCV 2023 Wenxuan Zhang, Paul Janson, Kai Yi, Ivan Skorokhodov, Mohamed Elhoseiny

The GRW loss augments the training by continually encouraging the model to generate realistic and characterized samples to represent the unseen space.

Novel Concepts Zero-Shot Learning

Imaginative Walks: Generative Random Walk Deviation Loss for Improved Unseen Learning Representation

1 code implementation20 Apr 2021 Divyansh Jha, Kai Yi, Ivan Skorokhodov, Mohamed Elhoseiny

By generating representations of unseen classes based on their semantic descriptions, e. g., attributes or text, generative ZSL attempts to differentiate unseen from seen categories.

Attribute Image Generation +1

Class Normalization for Zero-Shot Learning

no code implementations ICLR 2021 Ivan Skorokhodov, Mohamed Elhoseiny

Normalization techniques have proved to be a crucial ingredient of successful training in a traditional supervised learning regime.

Zero-Shot Learning

3D generation on ImageNet

no code implementations2 Mar 2023 Ivan Skorokhodov, Aliaksandr Siarohin, Yinghao Xu, Jian Ren, Hsin-Ying Lee, Peter Wonka, Sergey Tulyakov

Existing 3D-from-2D generators are typically designed for well-curated single-category datasets, where all the objects have (approximately) the same scale, 3D location, and orientation, and the camera always points to the center of the scene.

SATR: Zero-Shot Semantic Segmentation of 3D Shapes

no code implementations ICCV 2023 Ahmed Abdelreheem, Ivan Skorokhodov, Maks Ovsjanikov, Peter Wonka

We explore the task of zero-shot semantic segmentation of 3D shapes by using large-scale off-the-shelf 2D image recognition models.

Segmentation Semantic Segmentation +1

HyperHuman: Hyper-Realistic Human Generation with Latent Structural Diffusion

no code implementations12 Oct 2023 Xian Liu, Jian Ren, Aliaksandr Siarohin, Ivan Skorokhodov, Yanyu Li, Dahua Lin, Xihui Liu, Ziwei Liu, Sergey Tulyakov

Our model enforces the joint learning of image appearance, spatial relationship, and geometry in a unified network, where each branch in the model complements to each other with both structural awareness and textural richness.

Image Generation

4D-fy: Text-to-4D Generation Using Hybrid Score Distillation Sampling

no code implementations29 Nov 2023 Sherwin Bahmani, Ivan Skorokhodov, Victor Rong, Gordon Wetzstein, Leonidas Guibas, Peter Wonka, Sergey Tulyakov, Jeong Joon Park, Andrea Tagliasacchi, David B. Lindell

Recent breakthroughs in text-to-4D generation rely on pre-trained text-to-image and text-to-video models to generate dynamic 3D scenes.

Snap Video: Scaled Spatiotemporal Transformers for Text-to-Video Synthesis

no code implementations22 Feb 2024 Willi Menapace, Aliaksandr Siarohin, Ivan Skorokhodov, Ekaterina Deyneka, Tsai-Shien Chen, Anil Kag, Yuwei Fang, Aleksei Stoliar, Elisa Ricci, Jian Ren, Sergey Tulyakov

Since video content is highly redundant, we argue that naively bringing advances of image models to the video generation domain reduces motion fidelity, visual quality and impairs scalability.

Image Generation Text-to-Video Generation +1

Cannot find the paper you are looking for? You can Submit a new open access paper.