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20212023
most citedQwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

149 citations · 173 across the 9 of their papers we have counts for

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8 papers · 1 filter

cs.CV20237 cited

TouchStone: Evaluating Vision-Language Models by Language Models

Shuai Bai, Shusheng Yang, Jinze Bai +6

Large vision-language models (LVLMs) have recently witnessed rapid advancements, exhibiting a remarkable capacity for perceiving, understanding, and processing visual information b…

cs.CV2023149 cited

Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Jinze Bai, Shuai Bai, Shusheng Yang +6

In this work, we introduce the Qwen-VL series, a set of large-scale vision-language models (LVLMs) designed to perceive and understand both texts and images. Starting from the Qwen…

cs.CV20231 cited

ViTMatte: Boosting Image Matting with Pretrained Plain Vision Transformers

Jingfeng Yao, Xinggang Wang, Shusheng Yang +1

Recently, plain vision Transformers (ViTs) have shown impressive performance on various computer vision tasks, thanks to their strong modeling capacity and large-scale pretraining.…

cs.CV20231 cited

RILS: Masked Visual Reconstruction in Language Semantic Space

Shusheng Yang, Yixiao Ge, Kun Yi +4

Both masked image modeling (MIM) and natural language supervision have facilitated the progress of transferable visual pre-training. In this work, we seek the synergy between two p…

cs.CV20224 cited

Unleashing Vanilla Vision Transformer with Masked Image Modeling for Object Detection

Yuxin Fang, Shusheng Yang, Shijie Wang +3

We present an approach to efficiently and effectively adapt a masked image modeling (MIM) pre-trained vanilla Vision Transformer (ViT) for object detection, which is based on our t…

cs.CV20222 cited

Temporally Efficient Vision Transformer for Video Instance Segmentation

Shusheng Yang, Xinggang Wang, Yu Li +5

Recently vision transformer has achieved tremendous success on image-level visual recognition tasks. To effectively and efficiently model the crucial temporal information within a…