We explore the plain, non-hierarchical Vision Transformer (ViT) as a backbone network for object detection. This design enables the original ViT architecture to be fine-tuned for object detection without needing to redesign a hierarchical backbone for pre-training. With minimal adaptations for fine-...
牛人会为了提升模型效果加上各种花里胡哨的操作来提升一点点准确率,而神人为不断简化模型,通过很简单的模型来提升模型的效果,何凯明的这篇文章基于transformer的基础上进行模型优化,极大的提高了模型效果,简单看一张图就知道了,右侧表示的是新的plain backbone。当然这篇文章还是有另一个神人坐镇Ross Girshick, 哈哈是...
NeurIPS22 workshop:Exploring Transformer Backbones for Heterogeneous Treatment Effect Estimation 简简单单 21 人赞同了该文章 Treatment Effect Estimators(TEE): 离散、连续、结构化或与剂量相关的治疗。 1. Motivation:使用注意力层控制着治疗方法和协变量之间的相互作用,以利用潜在结果的结构相似性来进行混淆控制。
抛弃掉region-level和pixel-level prediction结构中的FPN(现在叫neck)一直是我们所有人的梦想（至少是我的...
COCO14WeakTrDeiT-SGoogle DriveGoogle Drive42.6% Citation If you find this repository/work helpful in your research, welcome to cite the paper and give a ⭐. @article{zhu2023weaktr, title={WeakTr: Exploring Plain Vision Transformer for Weakly-supervised Semantic Segmentation}, author={Lianghui...
Explor- ing plain vision transformer backbones for object detection. arXiv preprint arXiv:2203.16527, 2022. 5, 6 [61] Yanghao Li, Chao-Yuan Wu, Haoqi Fan, Karttikeya Mangalam, Bo Xiong, Jitendra Malik, and Christoph Feichtenhofer. Improved mul- tiscale vision...
TRANSFORMER modelsPLAINSMACHINE learningVIDEO codingAUTOMATED teller machinesThis paper investigates the capability of plain Vision Transformers (ViTs) for semantic segmentation using the encoder鈥揹ecoder framework and introduce SegViTv2. In this study, we introduce a novel Attention-to-Ma...
Context Length (M) 和 backbone选择 和Prompt Ensembling的比较 与精调模型进行比较 可解释性 总结 论文概况 今天带来的论文是《Exploring to Prompt for Vision-Language Models》,主题是基于CLIP的VLPT(Vision-Language Pre-Training)模型的提示学习(Prompt Learning),论文提出框架 CoOp(Context Optimization),通过一...
是不是可以尝试采用不带下采样的结构，也就是ViT这种？我在一些分割类任务上做过尝试，以ViT为backbone...