Next-Best-View Estimation based on Deep Reinforcement Learning for Active Object Classification

Related tags

Deep Learningnbv_rl
Overview

next_best_view_rl

Setup

  1. Clone the repository: git clone --recurse-submodules ...
  2. In 'third_party/zed-ros-wrapper': git checkout devel
  3. Install mujoco
  4. `sudo apt-get update && sudo apt-get install cmake libopenmpi-dev python3-dev zlib1g-dev libosmesa6-dev libgl1-mesa-glx libglfw3'
  5. Create virtual environment: conda create --name nbv_env python=3.7
  6. Activate virual environment: 'conda activate nbv_env'
  7. Install requirements: pip install -r requirements.txt
  8. Install setup.py: pip install -e .

Execution

  • modify configs in config with hydra framework
  • start RL training: python3 scripts/train.py
  • evaluate RL model: python3 scripts/evaluate.py
Owner
Christian Korbach
Christian Korbach
Learning Open-World Object Proposals without Learning to Classify

Learning Open-World Object Proposals without Learning to Classify Pytorch implementation for "Learning Open-World Object Proposals without Learning to

Dahun Kim 149 Dec 22, 2022
Asterisk is a framework to generate high-quality training datasets at scale

Asterisk is a framework to generate high-quality training datasets at scale

Mona Nashaat 44 Apr 25, 2022
An open-source Deep Learning Engine for Healthcare that aims to treat & prevent major diseases

AlphaCare Background AlphaCare is a work-in-progress, open-source Deep Learning Engine for Healthcare that aims to treat and prevent major diseases. T

Siraj Raval 44 Nov 05, 2022
shufflev2-yolov5:lighter, faster and easier to deploy

shufflev2-yolov5: lighter, faster and easier to deploy. Evolved from yolov5 and the size of model is only 1.7M (int8) and 3.3M (fp16). It can reach 10+ FPS on the Raspberry Pi 4B when the input size

pogg 1.5k Jan 05, 2023
Dataloader tools for language modelling

Installation: pip install lm_dataloader Design Philosophy A library to unify lm dataloading at large scale Simple interface, any tokenizer can be inte

5 Mar 25, 2022
这是一个facenet-pytorch的库,可以用于训练自己的人脸识别模型。

Facenet:人脸识别模型在Pytorch当中的实现 目录 性能情况 Performance 所需环境 Environment 注意事项 Attention 文件下载 Download 预测步骤 How2predict 训练步骤 How2train 参考资料 Reference 性能情况 训练数据

Bubbliiiing 210 Jan 06, 2023
Pytorch implementation for our ICCV 2021 paper "TRAR: Routing the Attention Spans in Transformers for Visual Question Answering".

TRAnsformer Routing Networks (TRAR) This is an official implementation for ICCV 2021 paper "TRAR: Routing the Attention Spans in Transformers for Visu

Ren Tianhe 49 Nov 10, 2022
PyTorch implementation for COMPLETER: Incomplete Multi-view Clustering via Contrastive Prediction (CVPR 2021)

Completer: Incomplete Multi-view Clustering via Contrastive Prediction This repo contains the code and data of the following paper accepted by CVPR 20

XLearning Group 72 Dec 07, 2022
OpenFace – a state-of-the art tool intended for facial landmark detection, head pose estimation, facial action unit recognition, and eye-gaze estimation.

OpenFace 2.2.0: a facial behavior analysis toolkit Over the past few years, there has been an increased interest in automatic facial behavior analysis

Tadas Baltrusaitis 5.8k Dec 31, 2022
An open-source project for applying deep learning to medical scenarios

Auto Vaidya An open source solution for creating end-end web app for employing the power of deep learning in various clinical scenarios like implant d

Smaranjit Ghose 18 May 29, 2022
CrossNorm and SelfNorm for Generalization under Distribution Shifts (ICCV 2021)

CrossNorm (CN) and SelfNorm (SN) (Accepted at ICCV 2021) This is the official PyTorch implementation of our CNSN paper, in which we propose CrossNorm

100 Dec 28, 2022
This repository contains PyTorch code for Robust Vision Transformers.

This repository contains PyTorch code for Robust Vision Transformers.

117 Dec 07, 2022
nn_builder lets you build neural networks with less boilerplate code

nn_builder lets you build neural networks with less boilerplate code. You specify the type of network you want and it builds it. Install pip install n

Petros Christodoulou 157 Nov 20, 2022
PyTorch implementation of Self-supervised Contrastive Regularization for DG (SelfReg)

SelfReg PyTorch official implementation of Self-supervised Contrastive Regularization for Domain Generalization (SelfReg, https://arxiv.org/abs/2104.0

64 Dec 16, 2022
ICNet for Real-Time Semantic Segmentation on High-Resolution Images, ECCV2018

ICNet for Real-Time Semantic Segmentation on High-Resolution Images by Hengshuang Zhao, Xiaojuan Qi, Xiaoyong Shen, Jianping Shi, Jiaya Jia, details a

Hengshuang Zhao 594 Dec 31, 2022
Pytorch implementation of four neural network based domain adaptation techniques: DeepCORAL, DDC, CDAN and CDAN+E. Evaluated on benchmark dataset Office31.

Deep-Unsupervised-Domain-Adaptation Pytorch implementation of four neural network based domain adaptation techniques: DeepCORAL, DDC, CDAN and CDAN+E.

Alan Grijalva 49 Dec 20, 2022
Stratified Transformer for 3D Point Cloud Segmentation (CVPR 2022)

Stratified Transformer for 3D Point Cloud Segmentation Xin Lai*, Jianhui Liu*, Li Jiang, Liwei Wang, Hengshuang Zhao, Shu Liu, Xiaojuan Qi, Jiaya Jia

DV Lab 195 Jan 01, 2023
Neural Koopman Lyapunov Control

Neural-Koopman-Lyapunov-Control Code for our paper: Neural Koopman Lyapunov Control Requirements dReal4: v4.19.02.1 PyTorch: 1.2.0 The learning framew

Vrushabh Zinage 6 Dec 24, 2022
On the Complementarity between Pre-Training and Back-Translation for Neural Machine Translation (Findings of EMNLP 2021))

PTvsBT On the Complementarity between Pre-Training and Back-Translation for Neural Machine Translation (Findings of EMNLP 2021) Citation Please cite a

Sunbow Liu 10 Nov 25, 2022
MQBench: Towards Reproducible and Deployable Model Quantization Benchmark

MQBench: Towards Reproducible and Deployable Model Quantization Benchmark We propose a benchmark to evaluate different quantization algorithms on vari

494 Dec 29, 2022