1 code implementation • 8 Apr 2024 • Kunpeng Song, Yizhe Zhu, Bingchen Liu, Qing Yan, Ahmed Elgammal, Xiao Yang
This approach effectively synergizes reference image and text prompt information to produce valuable image features, facilitating an image diffusion model.
no code implementations • 12 Feb 2024 • Yiyun He, Roman Vershynin, Yizhe Zhu
We present a polynomial-time algorithm for online differentially private synthetic data generation.
2 code implementations • 18 Nov 2023 • Di Chang, Yichun Shi, Quankai Gao, Jessica Fu, Hongyi Xu, Guoxian Song, Qing Yan, Yizhe Zhu, Xiao Yang, Mohammad Soleymani
In this work, we propose MagicPose, a diffusion-based model for 2D human pose and facial expression retargeting.
no code implementations • 9 Jun 2023 • Kameron Decker Harris, Oscar López, Angus Read, Yizhe Zhu
However, numerical experiments illustrate the dependence of the reconstruction error on the spectral gap for the practical max-quasinorm, ridge penalty, and Poisson loss minimization algorithms.
no code implementations • 26 May 2023 • Yiyun He, Thomas Strohmer, Roman Vershynin, Yizhe Zhu
Differentially private synthetic data provide a powerful mechanism to enable data analysis while protecting sensitive information about individuals.
1 code implementation • CVPR 2023 • Yufan Zhou, Bingchen Liu, Yizhe Zhu, Xiao Yang, Changyou Chen, Jinhui Xu
Unlike the baseline diffusion model used in DALL-E 2, our method seamlessly encodes prior knowledge of the pre-trained CLIP model in its diffusion process by designing a new initialization distribution and a new transition step of the diffusion.
Ranked #3 on Text-to-Image Generation on Multi-Modal-CelebA-HQ
no code implementations • 20 Nov 2022 • Daquan Zhou, Weimin WANG, Hanshu Yan, Weiwei Lv, Yizhe Zhu, Jiashi Feng
In specific, unlike existing works that directly train video models in the RGB space, we use a pre-trained VAE to map video clips into a low-dimensional latent space and learn the distribution of videos' latent codes via a diffusion model.
Ranked #10 on Text-to-Video Generation on MSR-VTT
no code implementations • 11 Nov 2022 • Zhichao Wang, Yizhe Zhu
Our analysis shows high-probability non-asymptotic concentration results for the training errors, cross-validations, and generalization errors of RFRR centered around their respective values for a kernel ridge regression (KRR).
1 code implementation • 14 Mar 2022 • Ludovic Stephan, Yizhe Zhu
We consider the community detection problem in a sparse $q$-uniform hypergraph $G$, assuming that $G$ is generated according to the Hypergraph Stochastic Block Model (HSBM).
no code implementations • 22 Dec 2021 • Ioana Dumitriu, Haixiao Wang, Yizhe Zhu
When the random hypergraph has bounded expected degrees, we provide a spectral algorithm that outputs a partition with at least a $\gamma$ fraction of the vertices classified correctly, where $\gamma\in (0. 5, 1)$ depends on the signal-to-noise ratio (SNR) of the model.
no code implementations • 29 Sep 2021 • Bingchen Liu, Yizhe Zhu, Xiao Yang, Ahmed Elgammal
The VQSN module facilitates a more delicate separation of posture and identity, while the training scheme ensures the VQSN module learns the pose-related representations.
no code implementations • 20 Sep 2021 • Zhichao Wang, Yizhe Zhu
As an application, we show that random feature regression induced by the empirical kernel achieves the same asymptotic performance as its limiting kernel regression under the ultra-wide regime.
7 code implementations • ICLR 2021 • Bingchen Liu, Yizhe Zhu, Kunpeng Song, Ahmed Elgammal
Training Generative Adversarial Networks (GAN) on high-fidelity images usually requires large-scale GPU-clusters and a vast number of training images.
Ranked #2 on Image Generation on ADE-Indoor
1 code implementation • 16 Dec 2020 • Bingchen Liu, Yizhe Zhu, Kunpeng Song, Ahmed Elgammal
Moreover, with the proposed sketch generator, the model shows a promising performance on style mixing and style transfer, which require synthesized images to be both style-consistent and semantically meaningful.
no code implementations • 26 Aug 2020 • Ioana Dumitriu, Yizhe Zhu
We compute the eigenvalue fluctuations of uniformly distributed random biregular bipartite graphs with fixed and growing degrees for a large class of analytic functions.
Probability Combinatorics
no code implementations • 27 May 2020 • Bingchen Liu, Kunpeng Song, Yizhe Zhu, Gerard de Melo, Ahmed Elgammal
Focusing on text-to-image (T2I) generation, we propose Text and Image Mutual-Translation Adversarial Networks (TIME), a lightweight but effective model that jointly learns a T2I generator G and an image captioning discriminator D under the Generative Adversarial Network framework.
no code implementations • CVPR 2020 • Yizhe Zhu, Martin Renqiang Min, Asim Kadav, Hans Peter Graf
We propose a sequential variational autoencoder to learn disentangled representations of sequential data (e. g., videos and audios) under self-supervision.
no code implementations • ICLR 2020 • Xingchao Peng, Zijun Huang, Yizhe Zhu, Kate Saenko
In this work, we present a principled approach to the problem of federated domain adaptation, which aims to align the representations learned among the different nodes with the data distribution of the target node.
2 code implementations • 23 Oct 2019 • Kameron Decker Harris, Yizhe Zhu
We provide a novel analysis of low-rank tensor completion based on hypergraph expanders.
1 code implementation • 26 May 2019 • Bingchen Liu, Yizhe Zhu, Zuohui Fu, Gerard de Melo, Ahmed Elgammal
Exploring the potential of GANs for unsupervised disentanglement learning, this paper proposes a novel GAN-based disentanglement framework with One-Hot Sampling and Orthogonal Regularization (OOGAN).
1 code implementation • ICCV 2019 • Yizhe Zhu, Jianwen Xie, Bingchen Liu, Ahmed Elgammal
We investigate learning feature-to-feature translator networks by alternating back-propagation as a general-purpose solution to zero-shot learning (ZSL) problems.
no code implementations • 11 Apr 2019 • Soumik Pal, Yizhe Zhu
We consider the community detection problem in sparse random hypergraphs.
no code implementations • NeurIPS 2019 • Yizhe Zhu, Jianwen Xie, Zhiqiang Tang, Xi Peng, Ahmed Elgammal
Zero-shot learning extends the conventional object classification to the unseen class recognition by introducing semantic representations of classes.
no code implementations • 16 Nov 2018 • Sam Cole, Yizhe Zhu
We consider the exact recovery problem in the hypergraph stochastic block model (HSBM) with $k$ blocks of equal size.
1 code implementation • 20 Aug 2018 • Zhiqiang Tang, Xi Peng, Shijie Geng, Yizhe Zhu, Dimitris N. Metaxas
We design a new connectivity pattern for the U-Net architecture.
Ranked #30 on Pose Estimation on MPII Human Pose
no code implementations • CVPR 2018 • Yizhe Zhu, Mohamed Elhoseiny, Bingchen Liu, Xi Peng, Ahmed Elgammal
Most existing zero-shot learning methods consider the problem as a visual semantic embedding one.
no code implementations • ICCV 2017 • Yizhe Zhu, Ahmed Elgammal
The exponentially increasing use of moving platforms for video capture introduces the urgent need to develop the general background subtraction algorithms with the capability to deal with the moving background.
no code implementations • CVPR 2017 • Mohamed Elhoseiny, Yizhe Zhu, Han Zhang, Ahmed Elgammal
We propose a learning framework that is able to connect text terms to its relevant parts and suppress connections to non-visual text terms without any part-text annotations.