Search Results for author: Menglei Chai

Found 19 papers, 10 papers with code

Quantized GAN for Complex Music Generation from Dance Videos

1 code implementation1 Apr 2022 Ye Zhu, Kyle Olszewski, Yu Wu, Panos Achlioptas, Menglei Chai, Yan Yan, Sergey Tulyakov

We present Dance2Music-GAN (D2M-GAN), a novel adversarial multi-modal framework that generates complex musical samples conditioned on dance videos.

Music Generation

R2L: Distilling Neural Radiance Field to Neural Light Field for Efficient Novel View Synthesis

1 code implementation31 Mar 2022 Huan Wang, Jian Ren, Zeng Huang, Kyle Olszewski, Menglei Chai, Yun Fu, Sergey Tulyakov

On the other hand, Neural Light Field (NeLF) presents a more straightforward representation over NeRF in novel view synthesis -- the rendering of a pixel amounts to one single forward pass without ray-marching.

Novel View Synthesis

NeROIC: Neural Rendering of Objects from Online Image Collections

no code implementations7 Jan 2022 Zhengfei Kuang, Kyle Olszewski, Menglei Chai, Zeng Huang, Panos Achlioptas, Sergey Tulyakov

We present a novel method to acquire object representations from online image collections, capturing high-quality geometry and material properties of arbitrary objects from photographs with varying cameras, illumination, and backgrounds.

Neural Rendering Novel View Synthesis

CLIP-NeRF: Text-and-Image Driven Manipulation of Neural Radiance Fields

no code implementations9 Dec 2021 Can Wang, Menglei Chai, Mingming He, Dongdong Chen, Jing Liao

Furthermore, we propose an inverse optimization method that accurately projects an input image to the latent codes for manipulation to enable editing on real images.

Novel View Synthesis

DisUnknown: Distilling Unknown Factors for Disentanglement Learning

1 code implementation ICCV 2021 Sitao Xiang, Yuming Gu, Pengda Xiang, Menglei Chai, Hao Li, Yajie Zhao, Mingming He

In this paper, we adopt a general setting where all factors that are hard to label or identify are encapsulated as a single unknown factor.

Disentanglement

Exemplar-Based 3D Portrait Stylization

no code implementations29 Apr 2021 Fangzhou Han, Shuquan Ye, Mingming He, Menglei Chai, Jing Liao

In the second texture style transfer stage, we focus on performing style transfer on the canonical texture by adopting a differentiable renderer to optimize the texture in a multi-view framework.

Style Transfer

Cross-Domain and Disentangled Face Manipulation with 3D Guidance

1 code implementation22 Apr 2021 Can Wang, Menglei Chai, Mingming He, Dongdong Chen, Jing Liao

Face image manipulation via three-dimensional guidance has been widely applied in various interactive scenarios due to its semantically-meaningful understanding and user-friendly controllability.

Domain Adaptation Image Manipulation

Motion Representations for Articulated Animation

2 code implementations CVPR 2021 Aliaksandr Siarohin, Oliver J. Woodford, Jian Ren, Menglei Chai, Sergey Tulyakov

To facilitate animation and prevent the leakage of the shape of the driving object, we disentangle shape and pose of objects in the region space.

Video Reconstruction

Diverse Semantic Image Synthesis via Probability Distribution Modeling

1 code implementation CVPR 2021 Zhentao Tan, Menglei Chai, Dongdong Chen, Jing Liao, Qi Chu, Bin Liu, Gang Hua, Nenghai Yu

In this paper, we propose a novel diverse semantic image synthesis framework from the perspective of semantic class distributions, which naturally supports diverse generation at semantic or even instance level.

Image-to-Image Translation

Efficient Semantic Image Synthesis via Class-Adaptive Normalization

1 code implementation8 Dec 2020 Zhentao Tan, Dongdong Chen, Qi Chu, Menglei Chai, Jing Liao, Mingming He, Lu Yuan, Gang Hua, Nenghai Yu

Spatially-adaptive normalization (SPADE) is remarkably successful recently in conditional semantic image synthesis \cite{park2019semantic}, which modulates the normalized activation with spatially-varying transformations learned from semantic layouts, to prevent the semantic information from being washed away.

Image Generation

MichiGAN: Multi-Input-Conditioned Hair Image Generation for Portrait Editing

1 code implementation30 Oct 2020 Zhentao Tan, Menglei Chai, Dongdong Chen, Jing Liao, Qi Chu, Lu Yuan, Sergey Tulyakov, Nenghai Yu

In this paper, we present MichiGAN (Multi-Input-Conditioned Hair Image GAN), a novel conditional image generation method for interactive portrait hair manipulation.

Conditional Image Generation

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.

Frame Style Transfer +2

Neural Hair Rendering

no code implementations ECCV 2020 Menglei Chai, Jian Ren, Sergey Tulyakov

Unlike existing supervised translation methods that require model-level similarity to preserve consistent structure representation for both real images and fake renderings, our method adopts an unsupervised solution to work on arbitrary hair models.

Translation

Human Motion Transfer from Poses in the Wild

no code implementations7 Apr 2020 Jian Ren, Menglei Chai, Sergey Tulyakov, Chen Fang, Xiaohui Shen, Jianchao Yang

In this paper, we tackle the problem of human motion transfer, where we synthesize novel motion video for a target person that imitates the movement from a reference video.

Translation

Rethinking Spatially-Adaptive Normalization

no code implementations6 Apr 2020 Zhentao Tan, Dongdong Chen, Qi Chu, Menglei Chai, Jing Liao, Mingming He, Lu Yuan, Nenghai Yu

Despite its impressive performance, a more thorough understanding of the true advantages inside the box is still highly demanded, to help reduce the significant computation and parameter overheads introduced by these new structures.

Image Generation

Revisiting Image Aesthetic Assessment via Self-Supervised Feature Learning

no code implementations26 Nov 2019 Kekai Sheng, Wei-Ming Dong, Menglei Chai, Guohui Wang, Peng Zhou, Feiyue Huang, Bao-Gang Hu, Rongrong Ji, Chongyang Ma

In this paper, we revisit the problem of image aesthetic assessment from the self-supervised feature learning perspective.

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