1 citations · 1 across the 5 of their papers we have counts for
7 papers
EmoVid: A Multimodal Emotion Video Dataset for Emotion-Centric Video Understanding and Generation
Zongyang Qiu, Bingyuan Wang, Xingbei Chen +2
Emotion plays a pivotal role in video-based expression, but existing video generation systems predominantly focus on low-level visual metrics while neglecting affective dimensions.…
Follow-Your-Instruction: A Comprehensive MLLM Agent for World Data Synthesis
Kunyu Feng, Yue Ma, Xinhua Zhang +9
With the growing demands of AI-generated content (AIGC), the need for high-quality, diverse, and scalable data has become increasingly crucial. However, collecting large-scale real…
MagicAnime: A Hierarchically Annotated, Multimodal and Multitasking Dataset with Benchmarks for Cartoon Animation Generation
Shuolin Xu, Bingyuan Wang, Zeyu Cai +5
Generating high-quality cartoon animations multimodal control is challenging due to the complexity of non-human characters, stylistically diverse motions and fine-grained emotions.…
Controllable Video Generation: A Survey
Yue Ma, Kunyu Feng, Zhongyuan Hu +19
With the rapid development of AI-generated content (AIGC), video generation has emerged as one of its most dynamic and impactful subfields. In particular, the advancement of video…
Follow-Your-Creation: Empowering 4D Creation through Video Inpainting
Yue Ma, Kunyu Feng, Xinhua Zhang +7
We introduce Follow-Your-Creation, a novel 4D video creation framework capable of both generating and editing 4D content from a single monocular video input. By leveraging a powerf…
Follow-Your-Color: Multi-Instance Sketch Colorization
Yinhan Zhang, Yue Ma, Bingyuan Wang +2
We present Follow-Your-Color, a diffusion-based framework for multi-instance sketch colorization. The production of multi-instance 2D line art colorization adheres to an industry-s…