3 citations · 6 across the 14 of their papers we have counts for
14 papers
Vidu S2: Real-Time Interactive, Editable, and Spatial Video Generation
Jintao Zhang, Kai Jiang, Jintao Chen +32
We present Vidu S2, which comprises Vidu S2-Avatar, a real-time interactive digital-character model, and Vidu S2-Editing, a real-time video editing model. Moreover, we explore the…
Vidu S1: A Real-Time Interactive Video Generation Model
Jintao Zhang, Kai Jiang, Jintao Chen +24
We introduce Vidu S1, a real-time interactive video generation model supporting voice control of digital characters. Users can control video generation content at any moment throug…
Motubrain: An Advanced World Action Model for Robot Control
Motubrain Team, Chendong Xiang, Fan Bao +17
Vision-Language-Action (VLA) models generalize semantically well but often lack fine-grained modeling of world dynamics. We present Motubrain, a unified World Action Model that joi…
Geometry-Aware Rotary Position Embedding for Consistent Video World Model
Chendong Xiang, Jiajun Liu, Jintao Zhang +7
Predictive world models that simulate future observations under explicit camera control are fundamental to interactive AI. Despite rapid advances, current systems lack spatial pers…
SpargeAttention2: Trainable Sparse Attention via Hybrid Top-k+Top-p Masking and Distillation Fine-Tuning
Jintao Zhang, Kai Jiang, Chendong Xiang +5
Many training-free sparse attention methods are effective for accelerating diffusion models. Recently, several works suggest that making sparse attention trainable can further incr…
Motus: A Unified Latent Action World Model
Hongzhe Bi, Hengkai Tan, Shenghao Xie +13
While a general embodied agent must function as a unified system, current methods are built on isolated models for understanding, world modeling, and control. This fragmentation pr…
Vidarc: Embodied Video Diffusion Model for Closed-loop Control
Yao Feng, Chendong Xiang, Xinyi Mao +7
Robotic arm manipulation in data-scarce settings is a highly challenging task due to the complex embodiment dynamics and diverse contexts. Recent video-based approaches have shown…
Vidar: Embodied Video Diffusion Model for Generalist Manipulation
Yao Feng, Hengkai Tan, Xinyi Mao +5
Scaling general-purpose manipulation to new robot embodiments remains challenging: each platform typically needs large, homogeneous demonstrations, and end-to-end pixel-to-action p…
SageAttention2++: A More Efficient Implementation of SageAttention2
Jintao Zhang, Xiaoming Xu, Jia Wei +5
The efficiency of attention is critical because its time complexity grows quadratically with sequence length. SageAttention2 addresses this by utilizing quantization to accelerate…
SpargeAttention: Accurate and Training-free Sparse Attention Accelerating Any Model Inference
Jintao Zhang, Chendong Xiang, Haofeng Huang +4
An efficient attention implementation is essential for large models due to its quadratic time complexity. Fortunately, attention commonly exhibits sparsity, i.e., many values in th…
Identifying and Solving Conditional Image Leakage in Image-to-Video Diffusion Model
Min Zhao, Hongzhou Zhu, Chendong Xiang +3
Diffusion models have obtained substantial progress in image-to-video generation. However, in this paper, we find that these models tend to generate videos with less motion than ex…
Vidu: a Highly Consistent, Dynamic and Skilled Text-to-Video Generator with Diffusion Models
Fan Bao, Chendong Xiang, Gang Yue +7
We introduce Vidu, a high-performance text-to-video generator that is capable of producing 1080p videos up to 16 seconds in a single generation. Vidu is a diffusion model with U-Vi…
CRM: Single Image to 3D Textured Mesh with Convolutional Reconstruction Model
Zhengyi Wang, Yikai Wang, Yifei Chen +6
Feed-forward 3D generative models like the Large Reconstruction Model (LRM) have demonstrated exceptional generation speed. However, the transformer-based methods do not leverage t…
A Closer Look at Parameter-Efficient Tuning in Diffusion Models
Chendong Xiang, Fan Bao, Chongxuan Li +2
Large-scale diffusion models like Stable Diffusion are powerful and find various real-world applications while customizing such models by fine-tuning is both memory and time ineffi…