Modify transform.py cd /datasets/transform.py Paris StreetView and Places2. Scale the image size to 256 x 256. Mask Dataset.Irregular masks are obtained fromIrregular Masksand classified based on their hole sizes relative to the entire image with an increment of 10%. ...
Video Snapshot Compressive Imaging (SCI) is a new imaging method based on compressive sensing. It encodes image sequences into a single snapshot measurement and then recovers the original high-speed video through reconstruction algorithms, which has the advantages of a low hardware cost and high ...
If this project helps your research or engineering, use\footnote{https://github.com/THUDM/SwissArmyTransformer}to mention us and recommendSwissArmyTransformerto others. The tutorial for contributing sat is on the way! The project is based on (a user of) DeepSpeed, Megatron-LM and Huggingface ...
Based on this, we propose an efficientimage restoration framework, dubbed SFHformer, which incorporates theFast Fourier Transform mechanism into Transformer architecture. Specifically, we design a dual domain hybrid structurefor multi-scale receptive fields modeling, in which the spatial domain and the ...
1, 3D object detection can be divided into three branches based on the different types of input data: the image branch, point cloud branch, and fusion branch. Traditional models take point clouds as input and utilize the spatial information of point clouds to generate 3D detection results. In...
When processing language, the brain is thought to deploy specialized computations to construct meaning from complex linguistic structures. Recently, artificial neural networks based on the Transformer architecture have revolutionized the field of natural
Thus, in this paper, we propose CrossT-Net (Cross Transformer Net), a novel cross-attention based loop closure detection network for LiDAR. CrossT-Net directly estimates the similarity between two frames by leveraging multi-class information maps, including range, intensity, and normal maps, to...
最近在github上看到一个博主开源的YOLOv7仓库都惊呆了,YOLOv6都还没出来怎么就到YOLOv7了 稍微看了下,原来作者是基于这两年来很火的transformer做的检测和分割模型,测试的效果都非常棒,比YOLOv5效果好很多。由此可见,基于Transformer based的检测模型才是未来。你会发现它学到的东西非常合理,比从一大堆boudingbox里面...
In addition to developing supervised transformer models, we have also showcased the utility of zero-shot-based scores, especially for predicting noncoding variant effects. Given that these zero-shot-based scores can be derived solely from genomic sequences, we encourage their application in nonhuman ...
General instructions for training, fine-tuning, evaluation, and exporting models for inference can be found in the [t5 repo](https://github.com/google-research/text-to-text-transfer-transformer). In order to use the additional tasks and mixtures provided in this library with the `t5_mesh_...