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20232026
most citedSora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models

105 citations · 129 across the 29 of their papers we have counts for

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Showing 2024 · cs.CVShow all

5 papers · 2 filters

cs.CV2024★ 4 cited

Biomedical SAM 2: Segment Anything in Biomedical Images and Videos

Zhiling Yan, Weixiang Sun, Rong Zhou +8

Medical image segmentation and video object segmentation are essential for diagnosing and analyzing diseases by identifying and measuring biological structures. Recent advances in…

cs.CV2024★ 3 cited

Bora: Biomedical Generalist Video Generation Model

Weixiang Sun, Xiaocao You, Ruizhe Zheng +5

Generative models hold promise for revolutionizing medical education, robot-assisted surgery, and data augmentation for medical AI development. Diffusion models can now generate re…

cs.CV2024

ViT-1.58b: Mobile Vision Transformers in the 1-bit Era

Zhengqing Yuan, Rong Zhou, Hongyi Wang +3

Vision Transformers (ViTs) have achieved remarkable performance in various image classification tasks by leveraging the attention mechanism to process image patches as tokens. Howe…

cs.CV2024★ 5 cited

Mora: Enabling Generalist Video Generation via A Multi-Agent Framework

Zhengqing Yuan, Yixin Liu, Yihan Cao +10

Text-to-video generation has made significant strides, but replicating the capabilities of advanced systems like OpenAI Sora remains challenging due to their closed-source nature.…

cs.CV2024★ 105 cited

Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models

Yixin Liu, Kai Zhang, Yuan Li +9

Sora is a text-to-video generative AI model, released by OpenAI in February 2024. The model is trained to generate videos of realistic or imaginative scenes from text instructions…