WebIn this work, we introduce Dual Attention Vision Transformers (DaViT), a simple yet effective vision transformer architecture that is able to capture global context while maintaining computational efficiency. We propose approaching the problem from an orthogonal angle: exploiting self-attention mechanisms with both "spatial tokens" and "channel ... WebFocalNet的四种模型配置，SRF和LRF分别表示小感受野和大感受野。 唯一的区别是焦点层的数量。 作者将本文的方法分别与基于ConvNet、Transformers和MLP的三组方法在ImageNet-1K和ImageNet-22K数据集上进行了比较。 作者还在目标检测及语义分割数据集上达到了良好的效果，这里不做赘述。 在上面，作者与Swin Transformer和Focal …

DaViT: Dual Attention Vision Transformer (ECCV 2024) - GitHub

WebNov 8, 2024 · With a 3x smaller model size and training data size, FocalNet achieves new state-of-the-art (SoTA) on one of the most challenging vision tasks: COCO object identification. It surpassed all previous Transformer models for the first time in the past two years, which is a significant accomplishment. WebHave a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community. thl11-r23

PyTorch Image Models - GitHub

WebModel card for focalnet_small_lrf.ms_in1k A FocalNet image classification model. Pretrained on ImageNet-1k by paper authors. Model Details Model Type: Image classification / feature backbone Model Stats: WebNov 21, 2024 · @rose-jinyang what @TorbenSDJohansen suggested will work in a pinch, the model is already pretty much timm style and should work well, but it always takes a bit of time to sort out the pretrained configs, fix various torchscript/FX issues, and integrate with the builder so the head adapation, etc works... I do plan to do that, just have a pile of … WebJul 24, 2024 · We propose ConvNeXt, a pure ConvNet model constructed entirely from standard ConvNet modules. ConvNeXt is accurate, efficient, scalable and very simple in design. Catalog ImageNet-1K Training Code ImageNet-22K Pre-training Code ImageNet-1K Fine-tuning Code Downstream Transfer (Detection, Segmentation) Code Image … thl-10-r23