ROS support for Velodyne 3D LIDARs

Related tags

Deep Learningvelodyne
Overview

Overview

Velodyne1 is a collection of ROS2 packages supporting Velodyne high definition 3D LIDARs3.

Warning:

The master branch normally contains code being tested for the next ROS release. It will not always work with every previous release. To check out the source for the most recent release, check out the tag <version> with the highest version number.

The current master branch works with ROS Kinetic and Melodic. CI builds are currently run for Kinetic and Melodic.

Image-Stitching - Panorama composition using SIFT Features and a custom implementaion of RANSAC algorithm

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Official implementation of DreamerPro: Reconstruction-Free Model-Based Reinforcement Learning with Prototypical Representations in TensorFlow 2

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Efficient 3D Backbone Network for Temporal Modeling

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This is a pytorch implementation of the NeurIPS paper GAN Memory with No Forgetting.

GAN Memory for Lifelong learning This is a pytorch implementation of the NeurIPS paper GAN Memory with No Forgetting. Please consider citing our paper

Miaoyun Zhao 43 Dec 27, 2022
[CVPR 2022 Oral] Rethinking Minimal Sufficient Representation in Contrastive Learning

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FG-transformer-TTS Fine-grained style control in transformer-based text-to-speech synthesis

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Li-Wei Chen 64 Dec 30, 2022
The pytorch implementation of SOKD (BMVC2021).

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Code for the Convolutional Vision Transformer (ConViT)

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Facebook Research 418 Jan 06, 2023
FedJAX is a library for developing custom Federated Learning (FL) algorithms in JAX.

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Anonymous implementation of KSL

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Everything you want about DP-Based Federated Learning, including Papers and Code. (Mechanism: Laplace or Gaussian, Dataset: femnist, shakespeare, mnist, cifar-10 and fashion-mnist. )

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Created as part of CS50 AI's coursework. This AI makes use of knowledge entailment to calculate the best probabilities to win Minesweeper.

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LERP : Label-dependent and event-guided interpretable disease risk prediction using EHRs

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Source code of the paper "Deep Learning of Latent Variable Models for Industrial Process Monitoring".

Source code of the paper "Deep Learning of Latent Variable Models for Industrial Process Monitoring".

Xiangyin Kong 7 Nov 08, 2022
Springer Link Download Module for Python

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Memory Defense: More Robust Classificationvia a Memory-Masking Autoencoder

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