69 citations · 129 across the 27 of their papers we have counts for
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cs.CV2024
OmniTokenizer: A Joint Image-Video Tokenizer for Visual Generation
Junke Wang, Yi Jiang, Zehuan Yuan +3
Tokenizer, serving as a translator to map the intricate visual data into a compact latent space, lies at the core of visual generative models. Based on the finding that existing to…
cs.CV2024
OmniVid: A Generative Framework for Universal Video Understanding
Junke Wang, Dongdong Chen, Chong Luo +4
The core of video understanding tasks, such as recognition, captioning, and tracking, is to automatically detect objects or actions in a video and analyze their temporal evolution.…
cs.CV2024
MouSi: Poly-Visual-Expert Vision-Language Models
Xiaoran Fan, Tao Ji, Changhao Jiang +21
Current large vision-language models (VLMs) often encounter challenges such as insufficient capabilities of a single visual component and excessively long visual tokens. These issu…