1 citations · 4 across the 16 of their papers we have counts for
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SwiftVideo: A Unified Framework for Few-Step Video Generation through Trajectory-Distribution Alignment
Yanxiao Sun, Jiafu Wu, Yun Cao +6
Diffusion-based or flow-based models have achieved significant progress in video synthesis but require multiple iterative sampling steps, which incurs substantial computational ove…
StrandDesigner: Towards Practical Strand Generation with Sketch Guidance
Na Zhang, Moran Li, Chengming Xu +6
Realistic hair strand generation is crucial for applications like computer graphics and virtual reality. While diffusion models can generate hairstyles from text or images, these i…
Visual Document Understanding and Reasoning: A Multi-Agent Collaboration Framework with Agent-Wise Adaptive Test-Time Scaling
Xinlei Yu, Chengming Xu, Zhangquan Chen +6
The dominant paradigm of monolithic scaling in Vision-Language Models (VLMs) is failing for understanding and reasoning in documents, yielding diminishing returns as it struggles w…
VTBench: Comprehensive Benchmark Suite Towards Real-World Virtual Try-on Models
Hu Xiaobin, Liang Yujie, Luo Donghao +5
While virtual try-on has achieved significant progress, evaluating these models towards real-world scenarios remains a challenge. A comprehensive benchmark is essential for three k…
Disentangle Identity, Cooperate Emotion: Correlation-Aware Emotional Talking Portrait Generation
Weipeng Tan, Chuming Lin, Chengming Xu +6
Recent advances in Talking Head Generation (THG) have achieved impressive lip synchronization and visual quality through diffusion models; yet existing methods struggle to generate…
When Preferences Diverge: Aligning Diffusion Models with Minority-Aware Adaptive DPO
Lingfan Zhang, Chen Liu, Chengming Xu +5
In recent years, the field of image generation has witnessed significant advancements, particularly in fine-tuning methods that align models with universal human preferences. This…
CrossVTON: Mimicking the Logic Reasoning on Cross-category Virtual Try-on guided by Tri-zone Priors
Donghao Luo, Yujie Liang, Xu Peng +6
Despite remarkable progress in image-based virtual try-on systems, generating realistic and robust fitting images for cross-category virtual try-on remains a challenging task. The…