13 papers · 1 filter
Group Editing: Edit Multiple Images in One Go
Yue Ma, Xinyu Wang, Qianli Ma +9
In this paper, we tackle the problem of performing consistent and unified modifications across a set of related images. This task is particularly challenging because these images m…
Manifold-Aware Exploration for Reinforcement Learning in Video Generation
Mingzhe Zheng, Weijie Kong, Yue Wu +9
Group Relative Policy Optimization (GRPO) methods for video generation like FlowGRPO remain far less reliable than their counterparts for language models and images. This gap arise…
Zero-shot Synthetic Video Realism Enhancement via Structure-aware Denoising
Yifan Wang, Liya Ji, Zhanghan Ke +3
We propose an approach to enhancing synthetic video realism, which can re-render synthetic videos from a simulator in photorealistic fashion. Our realism enhancement approach is a…
Enhancing Diffusion-based Restoration Models via Difficulty-Adaptive Reinforcement Learning with IQA Reward
Xiaogang Xu, Ruihang Chu, Jian Wang +6
Reinforcement Learning (RL) has recently been incorporated into diffusion models, e.g., tasks such as text-to-image. However, directly applying existing RL methods to diffusion-bas…
CML-Bench: A Framework for Evaluating and Enhancing LLM-Powered Movie Scripts Generation
Mingzhe Zheng, Dingjie Song, Guanyu Zhou +7
Large Language Models (LLMs) have demonstrated remarkable proficiency in generating highly structured texts. However, while exhibiting a high degree of structural organization, mov…
Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation
Harold Haodong Chen, Haojian Huang, Qifeng Chen +2
Recent advancements in video generation have enabled the creation of high-quality, visually compelling videos. However, generating videos that adhere to the laws of physics remains…