4 citations · 7 across the 13 of their papers we have counts for
7 papers · 1 filter
RDPM: Solve Diffusion Probabilistic Models via Recurrent Token Prediction
Xiaoping Wu, Jie Hu, Xiaoming Wei
Diffusion Probabilistic Models (DPMs) have emerged as the de facto approach for high-fidelity image synthesis, operating diffusion processes on continuous VAE latent, which signifi…
CharGen: High Accurate Character-Level Visual Text Generation Model with MultiModal Encoder
Lichen Ma, Tiezhu Yue, Pei Fu +4
Recently, significant advancements have been made in diffusion-based visual text generation models. Although the effectiveness of these methods in visual text rendering is rapidly…
High-Resolution Image Synthesis via Next-Token Prediction
Dengsheng Chen, Jie Hu, Tiezhu Yue +2
Recently, autoregressive models have demonstrated remarkable performance in class-conditional image generation. However, the application of next-token prediction to high-resolution…
Denoising with a Joint-Embedding Predictive Architecture
Dengsheng Chen, Jie Hu, Xiaoming Wei +1
Joint-embedding predictive architectures (JEPAs) have shown substantial promise in self-supervised representation learning, yet their application in generative modeling remains und…
Kangaroo: A Powerful Video-Language Model Supporting Long-context Video Input
Jiajun Liu, Yibing Wang, Hanghang Ma +6
Rapid advancements have been made in extending Large Language Models (LLMs) to Large Multi-modal Models (LMMs). However, extending input modality of LLMs to video data remains a ch…
Fine-gained Zero-shot Video Sampling
Dengsheng Chen, Jie Hu, Xiaoming Wei +1
Incorporating a temporal dimension into pretrained image diffusion models for video generation is a prevalent approach. However, this method is computationally demanding and necess…
Deformable 3D Shape Diffusion Model
Dengsheng Chen, Jie Hu, Xiaoming Wei +1
The Gaussian diffusion model, initially designed for image generation, has recently been adapted for 3D point cloud generation. However, these adaptations have not fully considered…