Curated list of resources about Data for Good, Data Science for Good, Data Science for Social Good, Data Science for Public Good, Data for Humanity.

RKN for sharing with outside collaborators

Unofficial "partial" implementation of https://arxiv.org/abs/2104.05358

High-Resolution Image Synthesis with Latent Diffusion Models

A paper list of some recent Transformer-based CV works.

(CVPR 2023) The official project of "3D Semantic Segmentation in the Wild: Learning Generalized Models for Adverse-Condition Point Clouds"

Official implementation of the CVPR 2023 paper "Novel Class Discovery for 3D Point Cloud Semantic Segmentation"

The open-source tool for building high-quality datasets and computer vision models

Lidar line downsampling for KITTI dataset, transfer lidar the number of lidar lines from 64 to 32, 16, 8, etc.

PillarNeXt: Rethinking Network Designs for 3D Object Detection in LiDAR Point Clouds (CVPR 2023)

Interact with your documents using the power of GPT, 100% privately, no data leaks

Virtual Sparse Convolution for Multimodal 3D Object Detection

(CVPR 2019) Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving

Annotation tool for labeling KITTI dataset 3D ground truth instance segmentation.

Tutorial for using Kitti dataset easily

An ultimately comprehensive paper list of Vision Transformer/Attention, including papers, codes, and related websites

LiDAR snowfall simulation

Code examples of point cloud processing in python.

A collection of loss functions for medical image segmentation

A game theoretic approach to explain the output of any machine learning model.

SESAME: Semantic Editing of Scenes by Adding, Manipulating or Erasing Objects

OpenCV Sample Code in C

Code for robust monocular depth estimation described in "Ranftl et. al., Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer, TPAMI 2022"

Slides and Jupyter notebooks for the Deep Learning lectures at Master Year 2 Data Science from Institut Polytechnique de Paris

The NASA Prognostic Model Package is a Python framework focused on defining and building models for prognostics (computation of remaining useful life) of engineering systems, and provides a set of …

[NeurIPS 2021]: Are Transformers More Robust Than CNNs? (Pytorch implementation & checkpoints)

Collect some papers about transformer with vision. Awesome Transformer with Computer Vision (CV)

Online Multi-Granularity Distillation for GAN Compression (ICCV2021)