110 citations · 127 across the 8 of their papers we have counts for
8 papers
Qwen Technical Report
Jinze Bai, Shuai Bai, Yunfei Chu +45
Large language models (LLMs) have revolutionized the field of artificial intelligence, enabling natural language processing tasks that were previously thought to be exclusive to hu…
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.…
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…
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…
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…
Relational Surrogate Loss Learning
Tao Huang, Zekang Li, Hua Lu +6
Evaluation metrics in machine learning are often hardly taken as loss functions, as they could be non-differentiable and non-decomposable, e.g., average precision and F1 score. Thi…