16 citations · 20 across the 3 of their papers we have counts for
3 papers
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.CV2023★ 16 cited
Florence-2: Advancing a Unified Representation for a Variety of Vision Tasks
Bin Xiao, Haiping Wu, Weijian Xu +6
We introduce Florence-2, a novel vision foundation model with a unified, prompt-based representation for a variety of computer vision and vision-language tasks. While existing larg…
cs.CV2023★ 4 cited
TinyCLIP: CLIP Distillation via Affinity Mimicking and Weight Inheritance
Kan Wu, Houwen Peng, Zhenghong Zhou +10
In this paper, we propose a novel cross-modal distillation method, called TinyCLIP, for large-scale language-image pre-trained models. The method introduces two core techniques: af…