6 citations · 7 across the 5 of their papers we have counts for
6 papers
LynnReal-Omni: Native multi-modal Video Generation for Agentic Visual Workflows
Xiaofeng Mao, Peijia Lin, Shaohao Rui +3
Video diffusion models are stochastic and hard to control: precise content often requires repeated sampling without guaranteed success, and long-horizon scenes drift in appearance,…
BiWM: Advancing Open-Source Interactive Video World Models with Bidirectional Autoregression
Shaohao Rui, Xiaofeng Mao, Zhanyu Zhang +6
Interactive video world models commonly convert bidirectional video generators into causal autoregressive systems through control fine-tuning, autoregressive training, causal initi…
VI3DRM:Towards meticulous 3D Reconstruction from Sparse Views via Photo-Realistic Novel View Synthesis
Hao Chen, Jiafu Wu, Ying Jin +7
Recently, methods like Zero-1-2-3 have focused on single-view based 3D reconstruction and have achieved remarkable success. However, their predictions for unseen areas heavily rely…
OSV: One Step is Enough for High-Quality Image to Video Generation
Xiaofeng Mao, Zhengkai Jiang, Fu-Yun Wang +5
Video diffusion models have shown great potential in generating high-quality videos, making them an increasingly popular focus. However, their inherent iterative nature leads to su…
MambaGesture: Enhancing Co-Speech Gesture Generation with Mamba and Disentangled Multi-Modality Fusion
Chencan Fu, Yabiao Wang, Jiangning Zhang +7
Co-speech gesture generation is crucial for producing synchronized and realistic human gestures that accompany speech, enhancing the animation of lifelike avatars in virtual enviro…
MDT-A2G: Exploring Masked Diffusion Transformers for Co-Speech Gesture Generation
Xiaofeng Mao, Zhengkai Jiang, Qilin Wang +7
Recent advancements in the field of Diffusion Transformers have substantially improved the generation of high-quality 2D images, 3D videos, and 3D shapes. However, the effectivenes…