21 citations · 41 across the 13 of their papers we have counts for
14 papers
Cubic Discrete Diffusion: Discrete Visual Generation on High-Dimensional Representation Tokens
Yuqing Wang, Chuofan Ma, Zhijie Lin +7
Visual generation with discrete tokens has gained significant attention as it enables a unified token prediction paradigm shared with language models, promising seamless multimodal…
Seaweed-7B: Cost-Effective Training of Video Generation Foundation Model
Team Seawead, Ceyuan Yang, Zhijie Lin +52
This technical report presents a cost-efficient strategy for training a video generation foundation model. We present a mid-sized research model with approximately 7 billion parame…
Bridging Continuous and Discrete Tokens for Autoregressive Visual Generation
Yuqing Wang, Zhijie Lin, Yao Teng +4
Autoregressive visual generation models typically rely on tokenizers to compress images into tokens that can be predicted sequentially. A fundamental dilemma exists in token repres…
Parallelized Autoregressive Visual Generation
Yuqing Wang, Shuhuai Ren, Zhijie Lin +6
Autoregressive models have emerged as a powerful approach for visual generation but suffer from slow inference speed due to their sequential token-by-token prediction process. In t…
LVD-2M: A Long-take Video Dataset with Temporally Dense Captions
Tianwei Xiong, Yuqing Wang, Daquan Zhou +3
The efficacy of video generation models heavily depends on the quality of their training datasets. Most previous video generation models are trained on short video clips, while rec…
Loong: Generating Minute-level Long Videos with Autoregressive Language Models
Yuqing Wang, Tianwei Xiong, Daquan Zhou +5
It is desirable but challenging to generate content-rich long videos in the scale of minutes. Autoregressive large language models (LLMs) have achieved great success in generating…
StoryDiffusion: Consistent Self-Attention for Long-Range Image and Video Generation
Yupeng Zhou, Daquan Zhou, Ming-Ming Cheng +2
For recent diffusion-based generative models, maintaining consistent content across a series of generated images, especially those containing subjects and complex details, presents…
PLLaVA : Parameter-free LLaVA Extension from Images to Videos for Video Dense Captioning
Lin Xu, Yilin Zhao, Daquan Zhou +3
Vision-language pre-training has significantly elevated performance across a wide range of image-language applications. Yet, the pre-training process for video-related tasks demand…
Magic-Me: Identity-Specific Video Customized Diffusion
Ze Ma, Daquan Zhou, Chun-Hsiao Yeh +6
Creating content with specified identities (ID) has attracted significant interest in the field of generative models. In the field of text-to-image generation (T2I), subject-driven…
MagicVideo-V2: Multi-Stage High-Aesthetic Video Generation
Weimin Wang, Jiawei Liu, Zhijie Lin +9
The growing demand for high-fidelity video generation from textual descriptions has catalyzed significant research in this field. In this work, we introduce MagicVideo-V2 that inte…
ChatAnything: Facetime Chat with LLM-Enhanced Personas
Yilin Zhao, Xinbin Yuan, Shanghua Gao +4
In this technical report, we target generating anthropomorphized personas for LLM-based characters in an online manner, including visual appearance, personality and tones, with onl…
MAgIC: Investigation of Large Language Model Powered Multi-Agent in Cognition, Adaptability, Rationality and Collaboration
Lin Xu, Zhiyuan Hu, Daquan Zhou +5
Large Language Models (LLMs) have significantly advanced natural language processing, demonstrating exceptional reasoning, tool usage, and memory capabilities. As their application…
EPIM: Efficient Processing-In-Memory Accelerators based on Epitome
Chenyu Wang, Zhen Dong, Daquan Zhou +4
The utilization of large-scale neural networks on Processing-In-Memory (PIM) accelerators encounters challenges due to constrained on-chip memory capacity. To tackle this issue, cu…
Low-Resolution Self-Attention for Semantic Segmentation
Yu-Huan Wu, Shi-Chen Zhang, Yun Liu +6
Semantic segmentation tasks naturally require high-resolution information for pixel-wise segmentation and global context information for class prediction. While existing vision tra…