3 citations · 5 across the 9 of their papers we have counts for
10 papers
FastVMT: Eliminating Redundancy in Video Motion Transfer
Yue Ma, Zhikai Wang, Tianhao Ren +9
Video motion transfer aims to synthesize videos by generating visual content according to a text prompt while transferring the motion pattern observed in a reference video. Recent…
InstanceAnimator: Multi-Instance Sketch Video Colorization
Yinhan Zhang, Yue Ma, Bingyuan Wang +5
We propose InstanceAnimator, a novel Diffusion Transformer framework for multi-instance sketch video colorization. Existing methods suffer from three core limitations: inflexible u…
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…
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-Motion: Video Motion Transfer via Efficient Spatial-Temporal Decoupled Finetuning
Yue Ma, Yulong Liu, Qiyuan Zhu +8
Recently, breakthroughs in the video diffusion transformer have shown remarkable capabilities in diverse motion generations. As for the motion-transfer task, current methods mainly…
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…
EEdit: Rethinking the Spatial and Temporal Redundancy for Efficient Image Editing
Zexuan Yan, Yue Ma, Chang Zou +3
Inversion-based image editing is rapidly gaining momentum while suffering from significant computation overhead, hindering its application in real-time interactive scenarios. In th…
DiT4Edit: Diffusion Transformer for Image Editing
Kunyu Feng, Yue Ma, Bingyuan Wang +4
Despite recent advances in UNet-based image editing, methods for shape-aware object editing in high-resolution images are still lacking. Compared to UNet, Diffusion Transformers (D…
Diffusion-Based Visual Art Creation: A Survey and New Perspectives
Bingyuan Wang, Qifeng Chen, Zeyu Wang
The integration of generative AI in visual art has revolutionized not only how visual content is created but also how AI interacts with and reflects the underlying domain knowledge…