33 citations · 49 across the 5 of their papers we have counts for
5 papers
Adapting LLaMA Decoder to Vision Transformer
Jiahao Wang, Wenqi Shao, Mengzhao Chen +7
This work examines whether decoder-only Transformers such as LLaMA, which were originally designed for large language models (LLMs), can be adapted to the computer vision field. We…
GPT4RoI: Instruction Tuning Large Language Model on Region-of-Interest
Shilong Zhang, Peize Sun, Shoufa Chen +6
Visual instruction tuning large language model(LLM) on image-text pairs has achieved general-purpose vision-language abilities. However, the lack of region-text pairs limits their…
DetCo: Unsupervised Contrastive Learning for Object Detection
Enze Xie, Jian Ding, Wenhai Wang +5
Unsupervised contrastive learning achieves great success in learning image representations with CNN. Unlike most recent methods that focused on improving accuracy of image classifi…
Scale Calibrated Training: Improving Generalization of Deep Networks via Scale-Specific Normalization
Zhuoran Yu, Aojun Zhou, Yukun Ma +3
Standard convolutional neural networks(CNNs) require consistent image resolutions in both training and testing phase. However, in practice, testing with smaller image sizes is nece…
SSN: Learning Sparse Switchable Normalization via SparsestMax
Wenqi Shao, Tianjian Meng, Jingyu Li +4
Normalization methods improve both optimization and generalization of ConvNets. To further boost performance, the recently-proposed switchable normalization (SN) provides a new per…