7 papers
Advancing Open-source World Models
Robbyant Team, Zelin Gao, Qiuyu Wang +21
We present LingBot-World, an open-sourced world simulator stemming from video generation. Positioned as a top-tier world model, LingBot-World offers the following features. (1) It…
The World is Your Canvas: Painting Promptable Events with Reference Images, Trajectories, and Text
Hanlin Wang, Hao Ouyang, Qiuyu Wang +12
We present WorldCanvas, a framework for promptable world events that enables rich, user-directed simulation by combining text, trajectories, and reference images. Unlike text-only…
MagicQuillV2: Precise and Interactive Image Editing with Layered Visual Cues
Zichen Liu, Yue Yu, Hao Ouyang +11
We propose MagicQuill V2, a novel system that introduces a \textbf{layered composition} paradigm to generative image editing, bridging the gap between the semantic power of diffusi…
Scaling Instruction-Based Video Editing with a High-Quality Synthetic Dataset
Qingyan Bai, Qiuyu Wang, Hao Ouyang +10
Instruction-based video editing promises to democratize content creation, yet its progress is severely hampered by the scarcity of large-scale, high-quality training data. We intro…
Benchmarking Large Vision-Language Models via Directed Scene Graph for Comprehensive Image Captioning
Fan Lu, Wei Wu, Kecheng Zheng +7
Generating detailed captions comprehending text-rich visual content in images has received growing attention for Large Vision-Language Models (LVLMs). However, few studies have dev…
Learning Visual Generative Priors without Text
Shuailei Ma, Kecheng Zheng, Ying Wei +7
Although text-to-image (T2I) models have recently thrived as visual generative priors, their reliance on high-quality text-image pairs makes scaling up expensive. We argue that gra…