MM1 and MMC Queue Simulation using python - Results and parameters in excel and csv files
Overview
An implementation of a sequence to sequence neural network using an encoder-decoder
Keras implementation of a sequence to sequence model for time series prediction using an encoder-decoder architecture. I created this post to share a
A state of the art of new lightweight YOLO model implemented by TensorFlow 2.
CSL-YOLO: A New Lightweight Object Detection System for Edge Computing This project provides a SOTA level lightweight YOLO called "Cross-Stage Lightwe
Code repository for Semantic Terrain Classification for Off-Road Autonomous Driving
BEVNet Datasets Datasets should be put inside data/. For example, data/semantic_kitti_4class_100x100. Training BEVNet-S Example: cd experiments bash t
Generate indoor scenes with Transformers
SceneFormer: Indoor Scene Generation with Transformers Initial code release for the Sceneformer paper, contains models, train and test scripts for the
Clockwork Variational Autoencoder
Clockwork Variational Autoencoders (CW-VAE) Vaibhav Saxena, Jimmy Ba, Danijar Hafner If you find this code useful, please reference in your paper: @ar
A brand new hub for Scene Graph Generation methods based on MMdetection (2021). The pipeline of from detection, scene graph generation to downstream tasks (e.g., image cpationing) is supported. Pytorch version implementation of HetH (ECCV 2020) and TopicSG (ICCV 2021) is included.
MMSceneGraph Introduction MMSceneneGraph is an open source code hub for scene graph generation as well as supporting downstream tasks based on the sce
Official code for NeurIPS 2021 paper "Towards Scalable Unpaired Virtual Try-On via Patch-Routed Spatially-Adaptive GAN"
Towards Scalable Unpaired Virtual Try-On via Patch-Routed Spatially-Adaptive GAN Official code for NeurIPS 2021 paper "Towards Scalable Unpaired Virtu
Aggragrating Nested Transformer Official Jax Implementation
NesT is a simple method, which aggragrates nested local transformers on image blocks. The idea makes vision transformers attain better accuracy, data efficiency, and convergence on the ImageNet bench
This is the code repository implementing the paper "TreePartNet: Neural Decomposition of Point Clouds for 3D Tree Reconstruction".
TreePartNet This is the code repository implementing the paper "TreePartNet: Neural Decomposition of Point Clouds for 3D Tree Reconstruction". Depende
Deep Learning for humans
Keras: Deep Learning for Python Under Construction In the near future, this repository will be used once again for developing the Keras codebase. For
Object-Centric Learning with Slot Attention
Slot Attention This is a re-implementation of "Object-Centric Learning with Slot Attention" in PyTorch (https://arxiv.org/abs/2006.15055). Requirement
[NeurIPS'21 Spotlight] PyTorch code for our paper "Aligned Structured Sparsity Learning for Efficient Image Super-Resolution"
ASSL This repository is for a new network pruning method (Aligned Structured Sparsity Learning, ASSL) for efficient single image super-resolution (SR)
The Habitat-Matterport 3D Research Dataset - the largest-ever dataset of 3D indoor spaces.
Habitat-Matterport 3D Dataset (HM3D) The Habitat-Matterport 3D Research Dataset is the largest-ever dataset of 3D indoor spaces. It consists of 1,000
A note taker for NVDA. Allows the user to create, edit, view, manage and export notes to different formats.
Quick Notetaker add-on for NVDA The Quick Notetaker add-on is a wonderful tool which allows writing notes quickly and easily anytime and from any app
PyTorch implementation for "Mining Latent Structures with Contrastive Modality Fusion for Multimedia Recommendation"
MIRCO PyTorch implementation for paper: Latent Structures Mining with Contrastive Modality Fusion for Multimedia Recommendation Dependencies Python 3.
Flexible Option Learning - NeurIPS 2021
Flexible Option Learning This repository contains code for the paper Flexible Option Learning presented as a Spotlight at NeurIPS 2021. The implementa
The implementation of FOLD-R++ algorithm
FOLD-R-PP The implementation of FOLD-R++ algorithm. The target of FOLD-R++ algorithm is to learn an answer set program for a classification task. Inst
Node for thenewboston digital currency network.
Project setup For project setup see INSTALL.rst Community Join the community to stay updated on the most recent developments, project roadmaps, and ra
NCVX (NonConVeX): A User-Friendly and Scalable Package for Nonconvex Optimization in Machine Learning.
The source code is temporariy removed, as we are solving potential copyright and license issues with GRANSO (http://www.timmitchell.com/software/GRANS
这是一个yolo3-tf2的源码,可以用于训练自己的模型。
YOLOV3:You Only Look Once目标检测模型在Tensorflow2当中的实现 目录 性能情况 Performance 所需环境 Environment 文件下载 Download 训练步骤 How2train 预测步骤 How2predict 评估步骤 How2eval 参考资料