This is the implementation of DGN on Pymarl, which could be trained by VDN or QMIX.
python3 src/main.py --config=vdn --env-config=sc2 with comm_flag=1.0
python3 src/main.py --config=qmix --env-config=sc2 with comm_flag=1.0
In the costumed starcraft.py, we decrease the sight range and communication range.
Person Re-identification Final project of Computer Vision Table of content Person Re-identification Table of content Students: Proposed method Dataset
NLG evaluation via Statistical Measures of Similarity: BaryScore, DepthScore, InfoLM Automatic Evaluation Metric described in the papers BaryScore (EM
BalancingGroups Code to replicate the experimental results from Simple data balancing baselines achieve competitive worst-group-accuracy. Replicating
VD-BERT: A Unified Vision and Dialog Transformer with BERT PyTorch Code for the following paper at EMNLP2020: Title: VD-BERT: A Unified Vision and Dia
Rotate-Yolov5 This repository is based on Ultralytics/yolov5, with adjustments to enable rotate prediction boxes. Section I. Description The codes are
Multi-Domain Incremental Learning for Semantic Segmentation This is the Pytorch implementation of our work "Multi-Domain Incremental Learning for Sema
trRosetta This package is a part of trRosetta protein structure prediction protocol developed in: Improved protein structure prediction using predicte
DIFFNet This repo is for Self-Supervised Monocular DepthEstimation with Internal Feature Fusion(arXiv), BMVC2021 A new backbone for self-supervised de
scc4onnx Very simple NCHW and NHWC conversion tool for ONNX. Change to the specified input order for each and every input OP. Also, change the channel
DAIN (Depth-Aware Video Frame Interpolation) Project | Paper Wenbo Bao, Wei-Sheng Lai, Chao Ma, Xiaoyun Zhang, Zhiyong Gao, and Ming-Hsuan Yang IEEE C
A python package adding basic hierarchal networks in pytorch for classification tasks. It implements a simple hierarchal network structure based on feed-backward outputs.
TF-Unet General purpose U-Network implemented in Keras for image segmentation Getting started • Training • Evaluation Getting started Looking for Jupy
ADD: Frequency Attention and Multi-View based Knowledge Distillation to Detect Low-Quality Compressed Deepfake Images Binh M. Le & Simon S. Woo, "ADD:
Not All Points Are Equal: Learning Highly Efficient Point-based Detectors for 3D LiDAR Point Clouds (CVPR 2022, Oral) This is the official implementat
really-awesome-semantic-segmentation A list of all papers on Semantic Segmentation and the datasets they use. This site is maintained by Holger Caesar
Gymjsp Gymjsp is an open source Python library, which uses the OpenAI Gym interface for easily instantiating and interacting with RL environments, and
GrailQA is a new large-scale, high-quality KBQA dataset with 64,331 questions annotated with both answers and corresponding logical forms in different syntax (i.e., SPARQL, S-expression, etc.). It ca
BEVNet Datasets Datasets should be put inside data/. For example, data/semantic_kitti_4class_100x100. Training BEVNet-S Example: cd experiments bash t
软件加密模块 requirement： Crypto,pycryptodome,pyqt5 本地加密信息为随机字符串 使用说明 命令行参数 -h 帮助 -checkWorking 检查是否能正常工作，后接1确认指令 -checkEndDate 检查截至日期，后接1确认指令 -activateCode
Overview Customer Segmentation is one the most important applications of unsupervised learning. Using clustering techniques, companies can identify th
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