6 papers
Native3D: End-to-End 3D Scene Generation via Unified Mesh-Texture Modeling and Semantic Alignment
Yibo Liu, Ziwei Zhang, Haozhou Pang +3
This paper presents Native3D, the first end-to-end 3D scene generation framework that completely bypasses 2D intermediate representations. Traditional approaches typically require…
RAP: Real-time Audio-driven Portrait Animation with Video Diffusion Transformer
Fangyu Du, Taiqing Li, Qian Qiao +7
Audio-driven portrait animation aims to synthesize realistic and natural talking head videos from an input audio signal and a single reference image. While existing methods achieve…
MSD-KMamba: Bidirectional Spatial-Aware Multi-Modal 3D Brain Segmentation via Multi-scale Self-Distilled Fusion Strategy
Dayu Tan, Ziwei Zhang, Yansan Su +4
Numerous CNN-Transformer hybrid models rely on high-complexity global attention mechanisms to capture long-range dependencies, which introduces non-linear computational complexity…
EEGDM: EEG Representation Learning via Generative Diffusion Model
Jia Hong Puah, Sim Kuan Goh, Ziwei Zhang +6
While electroencephalogram (EEG) has been a crucial tool for monitoring the brain and diagnosing neurological disorders (e.g., epilepsy), learning meaningful representations from r…
Marrying Autoregressive Transformer and Diffusion with Multi-Reference Autoregression
Dingcheng Zhen, Qian Qiao, Xu Zheng +6
We introduce TransDiff, the first image generation model that marries Autoregressive (AR) Transformer with diffusion models. In this joint modeling framework, TransDiff encodes lab…
Teller: Real-Time Streaming Audio-Driven Portrait Animation with Autoregressive Motion Generation
Dingcheng Zhen, Shunshun Yin, Shiyang Qin +5
In this work, we introduce the first autoregressive framework for real-time, audio-driven portrait animation, a.k.a, talking head. Beyond the challenge of lengthy animation times,…