focal-frequency-loss This repository will provide the official code for the following paper: Focal Frequency Loss for Generative ModelsLiming Jiang, Bo Dai, Wayne Wu and Chen Change LoyarXiv preprint, 2020. Abstract: Despite the remarkable success of generative models in creating photorealistic images using deep neural networks, gaps could still exist between the real and generated images, especially in the frequency domain. In this study, we find that narrowing the frequency domain gap can ameliorate the image synthesis quality further. To this […]

ParallelStencil.jl ParallelStencil empowers domain scientists to write architecture-agnostic high-level code for parallel high-performance stencil computations on GPUs and CPUs. Performance similar to CUDA C can be achieved, which is typically a large improvement over the performance reached when using only CUDA.jl Array programming. For example, a 2-D shallow ice solver presented at JuliaCon 2020 [1] achieved a nearly 20 times better performance than a corresponding CUDA.jl Array programming implementation; in absolute terms, it reached 70% of the theoretical upper performance […]

Detectron2 This repo contains the training configurations, code and trained models trained on PubLayNet dataset using Detectron2 implementation.PubLayNet is a very large dataset for document layout analysis (document segmentation). It can be used to trained semantic segmentation/Object detection models. NOTE Models are trained on a portion of the dataset (train-0.zip, train-1.zip, train-2.zip, train-3.zip) Trained on total 191,832 images Models are evaluated on dev.zip (~11,000 images) Backbone pretrained on COCO dataset is used but trained from scratch on PubLayNet dataset Trained […]

BENDR BErt-like Neurophysiological Data Representation. This repository contains the source code for reproducing, or extending the BERT-like self-supervision pre-training for EEG data from the article: BENDR: using transformers and a contrastive self-supervised learning task to learn from massive amounts of EEG data To run these scripts, you will need to use the DN3 project. We will try to keep this updated so that it works with the latest DN3 release. If you are just looking for the BENDR model, and […]

qd-3dt Monocular Quasi-Dense 3D Object Tracking (QD-3DT) is an online framework detects and tracks objects in 3D using quasi-dense object proposals from 2D images. Monocular Quasi-Dense 3D Object Tracking,Hou-Ning Hu, Yung-Hsu Yang, Tobias Fischer, Trevor Darrell, Fisher Yu, Min Sun,arXiv technical report (arXiv 2103.07351)Project Website (QD-3DT) @article{Hu2021QD3DT, author = {Hu, Hou-Ning and Yang, Yung-Hsu and Fischer, Tobias and Yu, Fisher and Darrell, Trevor and Sun, Min}, title = {Monocular Quasi-Dense 3D Object Tracking}, journal = {ArXiv:2103.07351}, year = {2021} } […]

kodiak A GitHub bot to automatically update and merge GitHub PRs. install app | documentation | web dashboard Automate your GitHub Pull Requests Auto Update – Keep your PRs up to date with master automatically Auto Merge – Add the automerge label to auto merge once CI and Approvals pass. Bot Collaboration – Combine Kodiak with a dependency bot (dependabot, snyk, greenskeeper.io) to automate updating of dependencies Installation Kodiak is available through the GitHub Marketplace. If you’d rather run Kodiak […]