Ye Zhu

Ye Zhu

Illinois Institute of Technology

H-index: 8

North America-United States

About Ye Zhu

Ye Zhu, With an exceptional h-index of 8 and a recent h-index of 8 (since 2020), a distinguished researcher at Illinois Institute of Technology, specializes in the field of Multimodal Learning, Generative Models, Computer Vision.

His recent articles reflect a diverse array of research interests and contributions to the field:

D: Scaling Up Deepfake Detection by Learning from Discrepancy

Mining and Unifying Heterogeneous Contrastive Relations for Weakly-Supervised Actor-Action Segmentation

Diffusion in Diffusion: Cyclic One-Way Diffusion for Text-Vision-Conditioned Generation

Supplementing Missing Visions via Dialog for Scene Graph Generations

Discrete Contrastive Diffusion for Cross-Modal Music and Image Generation

DETER: Detecting Edited Regions for Deterring Generative Manipulations

Unseen Image Synthesis with Diffusion Models

Discrete Diffusion Reward Guidance Methods for Offline Reinforcement Learning

Ye Zhu Information

University

Position

___

Citations(all)

149

Citations(since 2020)

149

Cited By

6

hIndex(all)

8

hIndex(since 2020)

8

i10Index(all)

6

i10Index(since 2020)

6

Email

University Profile Page

Google Scholar

Ye Zhu Skills & Research Interests

Multimodal Learning

Generative Models

Computer Vision

Top articles of Ye Zhu

D: Scaling Up Deepfake Detection by Learning from Discrepancy

arXiv preprint arXiv:2404.04584

2024/4/6

Ye Zhu
Ye Zhu

H-Index: 2

Yu Wu
Yu Wu

H-Index: 16

Mining and Unifying Heterogeneous Contrastive Relations for Weakly-Supervised Actor-Action Segmentation

2024

Diffusion in Diffusion: Cyclic One-Way Diffusion for Text-Vision-Conditioned Generation

2024/1

Supplementing Missing Visions via Dialog for Scene Graph Generations

2024/4/14

Discrete Contrastive Diffusion for Cross-Modal Music and Image Generation

2023

DETER: Detecting Edited Regions for Deterring Generative Manipulations

arXiv preprint arXiv:2312.10539

2023/12/16

Unseen Image Synthesis with Diffusion Models

arXiv preprint arXiv:2310.09213

2023/10/13

Discrete Diffusion Reward Guidance Methods for Offline Reinforcement Learning

2023/8/2

Denoising Diffusion Probabilistic Models to Predict the Density of Molecular Clouds

The Astrophysical Journal (APJ)

2023/4

Multimodal Learning and Generation Toward a Multisensory and Creative AI System

2023

Ye Zhu
Ye Zhu

H-Index: 2

Boundary Guided Learning-Free Semantic Control with Diffusion Models

2023/2/16

Vision+ X: A Survey on Multimodal Learning in the Light of Data

arXiv preprint arXiv:2210.02884

2022/10/5

Quantized GAN for Complex Music Generation from Dance Videos

2022/10/22

Skeleton Sequence and RGB Frame Based Multi-Modality Feature Fusion Network for Action Recognition

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM)

2022/3/4

Learning Audio-Visual Correlations from Variational Cross-Modal Generation

ICASSP

2021/2/5

Saying the Unseen: Video Descriptions via Dialog Agents

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)

2021/6/29

Hierarchical HMM for Eye Movement Classification

2020

Describing Unseen Videos via Multi-Modal Cooperative Dialog Agents

2020/8/18

See List of Professors in Ye Zhu University(Illinois Institute of Technology)

Co-Authors

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