activity
20202025
most citedFlorence: A New Foundation Model for Computer Vision

342 citations · 2k across the 44 of their papers we have counts for

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Showing 2024Show all

7 papers · 1 filter

cs.CV2024

Florence-VL: Enhancing Vision-Language Models with Generative Vision Encoder and Depth-Breadth Fusion

Jiuhai Chen, Jianwei Yang, Haiping Wu +4

We present Florence-VL, a new family of multimodal large language models (MLLMs) with enriched visual representations produced by Florence-2, a generative vision foundation model.…

cs.CV2024

DeepStack: Deeply Stacking Visual Tokens is Surprisingly Simple and Effective for LMMs

Lingchen Meng, Jianwei Yang, Rui Tian +4

Most large multimodal models (LMMs) are implemented by feeding visual tokens as a sequence into the first layer of a large language model (LLM). The resulting architecture is simpl…

cs.CV2024★ 107 cited

BiomedParse: a biomedical foundation model for image parsing of everything everywhere all at once

Theodore Zhao, Yu Gu, Jianwei Yang +12

Biomedical image analysis is fundamental for biomedical discovery in cell biology, pathology, radiology, and many other biomedical domains. Holistic image analysis comprises interd…

cs.CV2024

Matryoshka Multimodal Models

Mu Cai, Jianwei Yang, Jianfeng Gao +1

Large Multimodal Models (LMMs) such as LLaVA have shown strong performance in visual-linguistic reasoning. These models first embed images into a fixed large number of visual token…

cs.CV2024

Pix2Gif: Motion-Guided Diffusion for GIF Generation

Hitesh Kandala, Jianfeng Gao, Jianwei Yang

We present Pix2Gif, a motion-guided diffusion model for image-to-GIF (video) generation. We tackle this problem differently by formulating the task as an image translation problem…

cs.CL2024★ 40 cited

Towards a clinically accessible radiology foundation model: open-access and lightweight, with automated evaluation

Juan Manuel Zambrano Chaves, Shih-Cheng Huang, Yanbo Xu +24

The scaling laws and extraordinary performance of large foundation models motivate the development and utilization of such models in biomedicine. However, despite early promising r…

cs.CV2024★ 14 cited

Foundation Models for Biomedical Image Segmentation: A Survey

Ho Hin Lee, Yu Gu, Theodore Zhao +9

Recent advancements in biomedical image analysis have been significantly driven by the Segment Anything Model (SAM). This transformative technology, originally developed for genera…