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20232026
most citedOptimal Linear Subspace Search: Learning to Construct Fast and High-Quality Schedulers for Diffusion Models

5 citations · 10 across the 12 of their papers we have counts for

collaborators

12 papers

cs.CV2026

VIRAL: Visual In-Context Reasoning via Analogy in Diffusion Transformers

Zhiwen Li, Zhongjie Duan, Jinyan Ye +4

Replicating In-Context Learning (ICL) in computer vision remains challenging due to task heterogeneity. We propose \textbf{VIRAL}, a framework that elicits visual reasoning from a…

cs.LG2026

Spectral Evolution Search: Efficient Inference-Time Scaling for Reward-Aligned Image Generation

Jinyan Ye, Zhongjie Duan, Zhiwen Li +4

Inference-time scaling offers a versatile paradigm for aligning visual generative models with downstream objectives without parameter updates. However, existing approaches that opt…

cs.CV2025

AutoLoRA: Automatic LoRA Retrieval and Fine-Grained Gated Fusion for Text-to-Image Generation

Zhiwen Li, Zhongjie Duan, Die Chen +4

Despite recent advances in photorealistic image generation through large-scale models like FLUX and Stable Diffusion v3, the practical deployment of these architectures remains con…

cs.CV2025

AttriCtrl: Fine-Grained Control of Aesthetic Attribute Intensity in Diffusion Models

Die Chen, Zhongjie Duan, Zhiwen Li +4

Diffusion models have recently become the dominant paradigm for image generation, yet existing systems struggle to interpret and follow numeric instructions for adjusting semantic…

cs.CV2024

ArtAug: Enhancing Text-to-Image Generation through Synthesis-Understanding Interaction

Zhongjie Duan, Qianyi Zhao, Cen Chen +4

The emergence of diffusion models has significantly advanced image synthesis. The recent studies of model interaction and self-corrective reasoning approach in large language model…

cs.CV2024

ExVideo: Extending Video Diffusion Models via Parameter-Efficient Post-Tuning

Zhongjie Duan, Wenmeng Zhou, Cen Chen +2

Recently, advancements in video synthesis have attracted significant attention. Video synthesis models such as AnimateDiff and Stable Video Diffusion have demonstrated the practica…

cs.CV2024★ 1 cited

Diffutoon: High-Resolution Editable Toon Shading via Diffusion Models

Zhongjie Duan, Chengyu Wang, Cen Chen +2

Toon shading is a type of non-photorealistic rendering task of animation. Its primary purpose is to render objects with a flat and stylized appearance. As diffusion models have asc…

cs.CV2023

FastBlend: a Powerful Model-Free Toolkit Making Video Stylization Easier

Zhongjie Duan, Chengyu Wang, Cen Chen +3

With the emergence of diffusion models and rapid development in image processing, it has become effortless to generate fancy images in tasks such as style transfer and image editin…

cs.CL2023★ 1 cited

Learning Knowledge-Enhanced Contextual Language Representations for Domain Natural Language Understanding

Ruyao Xu, Taolin Zhang, Chengyu Wang +6

Knowledge-Enhanced Pre-trained Language Models (KEPLMs) improve the performance of various downstream NLP tasks by injecting knowledge facts from large-scale Knowledge Graphs (KGs)…

cs.CL2023★ 3 cited

PAI-Diffusion: Constructing and Serving a Family of Open Chinese Diffusion Models for Text-to-image Synthesis on the Cloud

Chengyu Wang, Zhongjie Duan, Bingyan Liu +4

Text-to-image synthesis for the Chinese language poses unique challenges due to its large vocabulary size, and intricate character relationships. While existing diffusion models ha…

cs.CV2023

DiffSynth: Latent In-Iteration Deflickering for Realistic Video Synthesis

Zhongjie Duan, Lizhou You, Chengyu Wang +4

In recent years, diffusion models have emerged as the most powerful approach in image synthesis. However, applying these models directly to video synthesis presents challenges, as…

cs.CV2023★ 5 cited

Optimal Linear Subspace Search: Learning to Construct Fast and High-Quality Schedulers for Diffusion Models

Zhongjie Duan, Chengyu Wang, Cen Chen +2

In recent years, diffusion models have become the most popular and powerful methods in the field of image synthesis, even rivaling human artists in artistic creativity. However, th…