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cs.CV2026

DiffusionAgent: Navigating Expert Models for Agentic Image Generation

Jie Qin, Jie Wu, Weifeng Chen +1

In the accelerating era of human-instructed visual content creation, diffusion models have demonstrated remarkable generative potential. Yet their deployment is constrained by a du…

cs.CV2025

OnlineVPO: Align Video Diffusion Model with Online Video-Centric Preference Optimization

Jiacheng Zhang, Jie Wu, Weifeng Chen +4

Video diffusion models (VDMs) have demonstrated remarkable capabilities in text-to-video (T2V) generation. Despite their success, VDMs still suffer from degraded image quality and…

cs.CV2024

Prompt-A-Video: Prompt Your Video Diffusion Model via Preference-Aligned LLM

Yatai Ji, Jiacheng Zhang, Jie Wu +9

Text-to-video models have made remarkable advancements through optimization on high-quality text-video pairs, where the textual prompts play a pivotal role in determining quality o…

cs.CV2024

Control-A-Video: Controllable Text-to-Video Diffusion Models with Motion Prior and Reward Feedback Learning

Weifeng Chen, Yatai Ji, Jie Wu +6

Recent advances in text-to-image (T2I) diffusion models have enabled impressive image generation capabilities guided by text prompts. However, extending these techniques to video g…

cs.CV2024

IDA-VLM: Towards Movie Understanding via ID-Aware Large Vision-Language Model

Yatai Ji, Shilong Zhang, Jie Wu +6

The rapid advancement of Large Vision-Language models (LVLMs) has demonstrated a spectrum of emergent capabilities. Nevertheless, current models only focus on the visual content of…

cs.CV2024

ID-Aligner: Enhancing Identity-Preserving Text-to-Image Generation with Reward Feedback Learning

Weifeng Chen, Jiacheng Zhang, Jie Wu +3

The rapid development of diffusion models has triggered diverse applications. Identity-preserving text-to-image generation (ID-T2I) particularly has received significant attention…