228 Repositories
Python parquet-benchmark Libraries
Current state of supervised and unsupervised depth completion methods
Awesome Depth Completion Table of Contents About Sparse-to-Dense Depth Completion Current State of Depth Completion Unsupervised VOID Benchmark Superv
Development kit for MIT Scene Parsing Benchmark
Development Kit for MIT Scene Parsing Benchmark [NEW!] Our PyTorch implementation is released in the following repository: https://github.com/hangzhao
Ultra-lightweight human body posture key point CNN model. ModelSize:2.3MB HUAWEI P40 NCNN benchmark: 6ms/img,
Ultralight-SimplePose Support NCNN mobile terminal deployment Based on MXNET(=1.5.1) GLUON(=0.7.0) framework Top-down strategy: The input image is t
A Large Scale Benchmark for Individual Treatment Effect Prediction and Uplift Modeling
large-scale-ITE-UM-benchmark This repository contains code and data to reproduce the results of the paper "A Large Scale Benchmark for Individual Trea
ClevrTex: A Texture-Rich Benchmark for Unsupervised Multi-Object Segmentation
ClevrTex This repository contains dataset generation code for ClevrTex benchmark from paper: ClevrTex: A Texture-Rich Benchmark for Unsupervised Multi
GNN-based Recommendation Benchmark
GRecX A Fair Benchmark for GNN-based Recommendation Homepage and Documentation Homepage: Documentation: Paper: GRecX: An Efficient and Unified Benchma
Repository for the electrical and ICT benchmark model developed in the ERIGrid 2.0 project.
Benchmark Model Electrical and ICT System This repository contains the documentation, code, and models for the electrical and ICT benchmark model deve
A benchmark of data-centric tasks from across the machine learning lifecycle.
A benchmark of data-centric tasks from across the machine learning lifecycle.
Natural Intelligence is still a pretty good idea.
Human Learn Machine Learning models should play by the rules, literally. Project Goal Back in the old days, it was common to write rule-based systems.
This is a tensorflow-based rotation detection benchmark, also called AlphaRotate.
AlphaRotate: A Rotation Detection Benchmark using TensorFlow Abstract AlphaRotate is maintained by Xue Yang with Shanghai Jiao Tong University supervi
This repository contains the needed resources to build the HIRID-ICU-Benchmark dataset
HiRID-ICU-Benchmark This repository contains the needed resources to build the HIRID-ICU-Benchmark dataset for which the manuscript can be found here.
Extracting knowledge graphs from language models as a diagnostic benchmark of model performance.
Interpreting Language Models Through Knowledge Graph Extraction Idea: How do we interpret what a language model learns at various stages of training?
[CoRL 2021] A robotics benchmark for cross-embodiment imitation.
x-magical x-magical is a benchmark extension of MAGICAL specifically geared towards cross-embodiment imitation. The tasks still provide the Demo/Test
AOT (Associating Objects with Transformers) in PyTorch
An efficient modular implementation of Associating Objects with Transformers for Video Object Segmentation in PyTorch
PyAF is an Open Source Python library for Automatic Time Series Forecasting built on top of popular pydata modules.
PyAF (Python Automatic Forecasting) PyAF is an Open Source Python library for Automatic Forecasting built on top of popular data science python module
A benchmark for the task of translation suggestion
WeTS: A Benchmark for Translation Suggestion Translation Suggestion (TS), which provides alternatives for specific words or phrases given the entire d
Code and models for "Pano3D: A Holistic Benchmark and a Solid Baseline for 360 Depth Estimation", OmniCV Workshop @ CVPR21.
Pano3D A Holistic Benchmark and a Solid Baseline for 360o Depth Estimation Pano3D is a new benchmark for depth estimation from spherical panoramas. We
EEGEyeNet is benchmark to evaluate ET prediction based on EEG measurements with an increasing level of difficulty
Introduction EEGEyeNet EEGEyeNet is a benchmark to evaluate ET prediction based on EEG measurements with an increasing level of difficulty. Overview T
Graph Robustness Benchmark: A scalable, unified, modular, and reproducible benchmark for evaluating the adversarial robustness of Graph Machine Learning.
Homepage | Paper | Datasets | Leaderboard | Documentation Graph Robustness Benchmark (GRB) provides scalable, unified, modular, and reproducible evalu
A map update dataset and benchmark
MUNO21 MUNO21 is a dataset and benchmark for machine learning methods that automatically update and maintain digital street map datasets. Previous dat
Datasets and source code for our paper Webly Supervised Fine-Grained Recognition: Benchmark Datasets and An Approach
Introduction Datasets and source code for our paper Webly Supervised Fine-Grained Recognition: Benchmark Datasets and An Approach Datasets: WebFG-496
Dataset and Code for ICCV 2021 paper "Real-world Video Super-resolution: A Benchmark Dataset and A Decomposition based Learning Scheme"
Dataset and Code for RealVSR Real-world Video Super-resolution: A Benchmark Dataset and A Decomposition based Learning Scheme Xi Yang, Wangmeng Xiang,
Repository for Multimodal AutoML Benchmark
Benchmarking Multimodal AutoML for Tabular Data with Text Fields Repository for the NeurIPS 2021 Dataset Track Submission "Benchmarking Multimodal Aut
Benchmark library for high-dimensional HPO of black-box models based on Weighted Lasso regression
LassoBench LassoBench is a library for high-dimensional hyperparameter optimization benchmarks based on Weighted Lasso regression. Note: LassoBench is
STS Benchmark comprises a selection of the English datasets used in the STS tasks organized in the context of SemEval between 2012 and 2017. The selection of datasets include text from image captions, news headlines and user forums.
stsb_multi_mt_en STS Benchmark comprises a selection of the English datasets used in the STS tasks organized in the context of SemEval between 2012 an
SW components and demos for visual kinship recognition. An emphasis is put on the FIW dataset-- data loaders, benchmarks, results in summary.
FIW Data Development Kit Table of Contents Introduction Families In the Wild Database Publications Organization To Do License Getting Involved Introdu
[IROS2021] NYU-VPR: Long-Term Visual Place Recognition Benchmark with View Direction and Data Anonymization Influences
NYU-VPR This repository provides the experiment code for the paper Long-Term Visual Place Recognition Benchmark with View Direction and Data Anonymiza
[v1 (ISBI'21) + v2] MedMNIST: A Large-Scale Lightweight Benchmark for 2D and 3D Biomedical Image Classification
MedMNIST Project (Website) | Dataset (Zenodo) | Paper (arXiv) | MedMNIST v1 (ISBI'21) Jiancheng Yang, Rui Shi, Donglai Wei, Zequan Liu, Lin Zhao, Bili
The Unsupervised Reinforcement Learning Benchmark (URLB)
The Unsupervised Reinforcement Learning Benchmark (URLB) URLB provides a set of leading algorithms for unsupervised reinforcement learning where agent
A new benchmark for Icon Question Answering (IconQA) and a large-scale icon dataset Icon645.
IconQA About IconQA is a new diverse abstract visual question answering dataset that highlights the importance of abstract diagram understanding and c
Codebase for the self-supervised goal reaching benchmark introduced in the LEXA paper
LEXA Benchmark Codebase for the self-supervised goal reaching benchmark introduced in the LEXA paper (Discovering and Achieving Goals via World Models
NAS-HPO-Bench-II is the first benchmark dataset for joint optimization of CNN and training HPs.
NAS-HPO-Bench-II API Overview NAS-HPO-Bench-II is the first benchmark dataset for joint optimization of CNN and training HPs. It helps a fair and low-
A MNIST-like fashion product database. Benchmark
Fashion-MNIST Table of Contents Why we made Fashion-MNIST Get the Data Usage Benchmark Visualization Contributing Contact Citing Fashion-MNIST License
Flickr-Faces-HQ (FFHQ) is a high-quality image dataset of human faces, originally created as a benchmark for generative adversarial networks (GAN)
Flickr-Faces-HQ Dataset (FFHQ) Flickr-Faces-HQ (FFHQ) is a high-quality image dataset of human faces, originally created as a benchmark for generative
image scene graph generation benchmark
Scene Graph Benchmark in PyTorch 1.7 This project is based on maskrcnn-benchmark Highlights Upgrad to pytorch 1.7 Multi-GPU training and inference Bat
BEAMetrics: Benchmark to Evaluate Automatic Metrics in Natural Language Generation
BEAMetrics: Benchmark to Evaluate Automatic Metrics in Natural Language Generation Installing The Dependencies $ conda create --name beametrics python
Strawberry Benchmark With Python
Strawberry benchmarks these benchmarks have been made to compare the performance of dataloaders and joined database queries. How to use You can run th
Repository for the Bias Benchmark for QA dataset.
BBQ Repository for the Bias Benchmark for QA dataset. Authors: Alicia Parrish, Angelica Chen, Nikita Nangia, Vishakh Padmakumar, Jason Phang, Jana Tho
A Python library for adversarial machine learning focusing on benchmarking adversarial robustness.
ARES This repository contains the code for ARES (Adversarial Robustness Evaluation for Safety), a Python library for adversarial machine learning rese
Benchmark tools for Compressive LiDAR-to-map registration
Benchmark tools for Compressive LiDAR-to-map registration This repo contains the released version of code and datasets used for our IROS 2021 paper: "
LOT: A Benchmark for Evaluating Chinese Long Text Understanding and Generation
LOT: A Benchmark for Evaluating Chinese Long Text Understanding and Generation Tasks | Datasets | LongLM | Baselines | Paper Introduction LOT is a ben
This repository contains a set of benchmarks of different implementations of Parquet (storage format) - Arrow (in-memory format).
Parquet benchmarks This repository contains a set of benchmarks of different implementations of Parquet (storage format) - Arrow (in-memory format).
Repository for the Bias Benchmark for QA dataset.
BBQ Repository for the Bias Benchmark for QA dataset. Authors: Alicia Parrish, Angelica Chen, Nikita Nangia, Vishakh Padmakumar, Jason Phang, Jana Tho
Benchmark datasets, data loaders, and evaluators for graph machine learning
Overview The Open Graph Benchmark (OGB) is a collection of benchmark datasets, data loaders, and evaluators for graph machine learning. Datasets cover
Repository for benchmarking graph neural networks
Benchmarking Graph Neural Networks Updates Nov 2, 2020 Project based on DGL 0.4.2. See the relevant dependencies defined in the environment yml files
PyTorch implementation of paper “Unbiased Scene Graph Generation from Biased Training”
A new codebase for popular Scene Graph Generation methods (2020). Visualization & Scene Graph Extraction on custom images/datasets are provided. It's also a PyTorch implementation of paper “Unbiased Scene Graph Generation from Biased Training CVPR 2020”
The self-supervised goal reaching benchmark introduced in Discovering and Achieving Goals via World Models
Lexa-Benchmark Codebase for the self-supervised goal reaching benchmark introduced in 'Discovering and Achieving Goals via World Models'. Setup Create
ImageNet-CoG is a benchmark for concept generalization. It provides a full evaluation framework for pre-trained visual representations which measure how well they generalize to unseen concepts.
The ImageNet-CoG Benchmark Project Website Paper (arXiv) Code repository for the ImageNet-CoG Benchmark introduced in the paper "Concept Generalizatio
This repository contains all data used for writing a research paper Multiple Object Trackers in OpenCV: A Benchmark, presented in ISIE 2021 conference in Kyoto, Japan.
OpenCV-Multiple-Object-Tracking Python is version 3.6.7 to install opencv: pip uninstall opecv-python pip uninstall opencv-contrib-python pip install
New approach to benchmark VQA models
VQA Benchmarking This repository contains the web application & the python interface to evaluate VQA models. Documentation Please see the documentatio
Python suite to construct benchmark machine learning datasets from the MIMIC-III clinical database.
MIMIC-III Benchmarks Python suite to construct benchmark machine learning datasets from the MIMIC-III clinical database. Currently, the benchmark data
Starter Code for VALUE benchmark
StarterCode for VALUE Benchmark This is the starter code for VALUE Benchmark [website], [paper]. This repository currently supports all baseline model
LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation (NeurIPS2021 Benchmark and Dataset Track)
LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation by Junjue Wang, Zhuo Zheng, Ailong Ma, Xiaoyan Lu, and Yanfei Zh
Official code of paper: MovingFashion: a Benchmark for the Video-to-Shop Challenge
SEAM Match-RCNN Official code of MovingFashion: a Benchmark for the Video-to-Shop Challenge paper Installation Requirements: Pytorch 1.5.1 or more rec
LexGLUE: A Benchmark Dataset for Legal Language Understanding in English
LexGLUE: A Benchmark Dataset for Legal Language Understanding in English ⚖️ 🏆 🧑🎓 👩⚖️ Dataset Summary Inspired by the recent widespread use of th
ProFuzzBench - A Benchmark for Stateful Protocol Fuzzing
ProFuzzBench - A Benchmark for Stateful Protocol Fuzzing ProFuzzBench is a benchmark for stateful fuzzing of network protocols. It includes a suite of
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.
Benchmark a WebSocket server's message throughput ⌛
📻 WebSocket Benchmarker ⌚ Message throughput is how fast a WebSocket server can parse and respond to a message. Some people consider this to be a goo
WRENCH: Weak supeRvision bENCHmark
🔧 What is it? Wrench is a benchmark platform containing diverse weak supervision tasks. It also provides a common and easy framework for development
Benchmark for Answering Existential First Order Queries with Single Free Variable
EFO-1-QA Benchmark for First Order Query Estimation on Knowledge Graphs This repository contains an entire pipeline for the EFO-1-QA benchmark. EFO-1
Silero Models: pre-trained speech-to-text, text-to-speech models and benchmarks made embarrassingly simple
Silero Models: pre-trained speech-to-text, text-to-speech models and benchmarks made embarrassingly simple
Official code for 'Robust Siamese Object Tracking for Unmanned Aerial Manipulator' and offical introduction to UAMT100 benchmark
SiamSA: Robust Siamese Object Tracking for Unmanned Aerial Manipulator Demo video 📹 Our video on Youtube and bilibili demonstrates the evaluation of
wireguard-config-benchmark is a python script that benchmarks the download speeds for the connections defined in one or more wireguard config files
wireguard-config-benchmark is a python script that benchmarks the download speeds for the connections defined in one or more wireguard config files. If multiple configs are benchmarked it will output a file ranking them from fastest to slowest.
This is the official code for the paper "Tracker Meets Night: A Transformer Enhancer for UAV Tracking".
SCT This is the official code for the paper "Tracker Meets Night: A Transformer Enhancer for UAV Tracking" The spatial-channel Transformer (SCT) enhan
Phy-Q: A Benchmark for Physical Reasoning
Phy-Q: A Benchmark for Physical Reasoning Cheng Xue*, Vimukthini Pinto*, Chathura Gamage* Ekaterina Nikonova, Peng Zhang, Jochen Renz School of Comput
My published benchmark for a Kaggle Simulations Competition
Lux AI Working Title Bot Please refer to the Kaggle notebook for the comment section. The comment section contains my explanation on my code structure
Model Quantization Benchmark
MQBench Update V0.0.2 Fix academic prepare setting. More deployable prepare process. Fix setup.py. Fix deploy on SNPE. Fix convert_deploy bug. Add Qua
Dataset and Code for ICCV 2021 paper "Real-world Video Super-resolution: A Benchmark Dataset and A Decomposition based Learning Scheme"
Dataset and Code for RealVSR Real-world Video Super-resolution: A Benchmark Dataset and A Decomposition based Learning Scheme Xi Yang, Wangmeng Xiang,
A novel benchmark dataset for Monocular Layout prediction
AutoLay AutoLay: Benchmarking Monocular Layout Estimation Kaustubh Mani, N. Sai Shankar, J. Krishna Murthy, and K. Madhava Krishna Abstract In this pa
CPU benchmark by calculating Pi, powered by Python3
cpu-benchmark Info: CPU benchmark by calculating Pi, powered by Python 3. Algorithm The program calculates pi with an accuracy of 10,000 decimal place
The CLRS Algorithmic Reasoning Benchmark
Learning representations of algorithms is an emerging area of machine learning, seeking to bridge concepts from neural networks with classical algorithms.
CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms
CARLA - Counterfactual And Recourse Library CARLA is a python library to benchmark counterfactual explanation and recourse models. It comes out-of-the
Transfer Learning Shootout for PyTorch's model zoo (torchvision)
pytorch-retraining Transfer Learning shootout for PyTorch's model zoo (torchvision). Load any pretrained model with custom final layer (num_classes) f
WRENCH: Weak supeRvision bENCHmark
🔧 What is it? Wrench is a benchmark platform containing diverse weak supervision tasks. It also provides a common and easy framework for development
[Preprint] "Bag of Tricks for Training Deeper Graph Neural Networks A Comprehensive Benchmark Study" by Tianlong Chen*, Kaixiong Zhou*, Keyu Duan, Wenqing Zheng, Peihao Wang, Xia Hu, Zhangyang Wang
Bag of Tricks for Training Deeper Graph Neural Networks: A Comprehensive Benchmark Study Codes for [Preprint] Bag of Tricks for Training Deeper Graph
Pip-package for trajectory benchmarking from "Be your own Benchmark: No-Reference Trajectory Metric on Registered Point Clouds", ECMR'21
Map Metrics for Trajectory Quality Map metrics toolkit provides a set of metrics to quantitatively evaluate trajectory quality via estimating consiste
HDR Video Reconstruction: A Coarse-to-fine Network and A Real-world Benchmark Dataset (ICCV 2021)
Code for HDR Video Reconstruction HDR Video Reconstruction: A Coarse-to-fine Network and A Real-world Benchmark Dataset (ICCV 2021) Guanying Chen, Cha
FedScale: Benchmarking Model and System Performance of Federated Learning
FedScale: Benchmarking Model and System Performance of Federated Learning (Paper) This repository contains scripts and instructions of building FedSca
ALFRED - A Benchmark for Interpreting Grounded Instructions for Everyday Tasks
ALFRED A Benchmark for Interpreting Grounded Instructions for Everyday Tasks Mohit Shridhar, Jesse Thomason, Daniel Gordon, Yonatan Bisk, Winson Han,
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
Disfl-QA: A Benchmark Dataset for Understanding Disfluencies in Question Answering
Disfl-QA is a targeted dataset for contextual disfluencies in an information seeking setting, namely question answering over Wikipedia passages. Disfl-QA builds upon the SQuAD-v2 (Rajpurkar et al., 2018) dataset, where each question in the dev set is annotated to add a contextual disfluency using the paragraph as a source of distractors.
The dataset and source code for our paper: "Did You Ask a Good Question? A Cross-Domain Question IntentionClassification Benchmark for Text-to-SQL"
TriageSQL The dataset and source code for our paper: "Did You Ask a Good Question? A Cross-Domain Question Intention Classification Benchmark for Text
Benchmark for evaluating open-ended generation
OpenMEVA Contributed by Jian Guan, Zhexin Zhang. Thank Jiaxin Wen for DeBugging. OpenMEVA is a benchmark for evaluating open-ended story generation me
ManiSkill-Learn is a framework for training agents on SAPIEN Open-Source Manipulation Skill Challenge (ManiSkill Challenge), a large-scale learning-from-demonstrations benchmark for object manipulation.
ManiSkill-Learn ManiSkill-Learn is a framework for training agents on SAPIEN Open-Source Manipulation Skill Challenge, a large-scale learning-from-dem
KLUE-baseline contains the baseline code for the Korean Language Understanding Evaluation (KLUE) benchmark.
KLUE Baseline Korean(한국어) KLUE-baseline contains the baseline code for the Korean Language Understanding Evaluation (KLUE) benchmark. See our paper fo
SAPIEN Manipulation Skill Benchmark
ManiSkill Benchmark SAPIEN Manipulation Skill Benchmark (abbreviated as ManiSkill, pronounced as "Many Skill") is a large-scale learning-from-demonstr
Few-shot NLP benchmark for unified, rigorous eval
FLEX FLEX is a benchmark and framework for unified, rigorous few-shot NLP evaluation. FLEX enables: First-class NLP support Support for meta-training
[IJCAI-2021] A benchmark of data-free knowledge distillation from paper "Contrastive Model Inversion for Data-Free Knowledge Distillation"
DataFree A benchmark of data-free knowledge distillation from paper "Contrastive Model Inversion for Data-Free Knowledge Distillation" Authors: Gongfa
An open-access benchmark and toolbox for electricity price forecasting
epftoolbox The epftoolbox is the first open-access library for driving research in electricity price forecasting. Its main goal is to make available a
MVP Benchmark for Multi-View Partial Point Cloud Completion and Registration
MVP Benchmark: Multi-View Partial Point Clouds for Completion and Registration [NEWS] 2021-07-12 [NEW 🎉 ] The submission on Codalab starts! 2021-07-1
Generic Event Boundary Detection: A Benchmark for Event Segmentation
Generic Event Boundary Detection: A Benchmark for Event Segmentation We release our data annotation & baseline codes for detecting generic event bound
Official Implement of CVPR 2021 paper “Cross-Modal Collaborative Representation Learning and a Large-Scale RGBT Benchmark for Crowd Counting”
RGBT Crowd Counting Lingbo Liu, Jiaqi Chen, Hefeng Wu, Guanbin Li, Chenglong Li, Liang Lin. "Cross-Modal Collaborative Representation Learning and a L
This is the official repository for evaluation on the NoW Benchmark Dataset. The goal of the NoW benchmark is to introduce a standard evaluation metric to measure the accuracy and robustness of 3D face reconstruction methods from a single image under variations in viewing angle, lighting, and common occlusions.
NoW Evaluation This is the official repository for evaluation on the NoW Benchmark Dataset. The goal of the NoW benchmark is to introduce a standard e
Baseline model for "GraspNet-1Billion: A Large-Scale Benchmark for General Object Grasping" (CVPR 2020)
GraspNet Baseline Baseline model for "GraspNet-1Billion: A Large-Scale Benchmark for General Object Grasping" (CVPR 2020). [paper] [dataset] [API] [do
NAS Benchmark in "Prioritized Architecture Sampling with Monto-Carlo Tree Search", CVPR2021
NAS-Bench-Macro This repository includes the benchmark and code for NAS-Bench-Macro in paper "Prioritized Architecture Sampling with Monto-Carlo Tree
A Neural Language Style Transfer framework to transfer natural language text smoothly between fine-grained language styles like formal/casual, active/passive, and many more. Created by Prithiviraj Damodaran. Open to pull requests and other forms of collaboration.
Styleformer A Neural Language Style Transfer framework to transfer natural language text smoothly between fine-grained language styles like formal/cas
modelvshuman is a Python library to benchmark the gap between human and machine vision
modelvshuman is a Python library to benchmark the gap between human and machine vision. Using this library, both PyTorch and TensorFlow models can be evaluated on 17 out-of-distribution datasets with high-quality human comparison data.
中文医疗信息处理基准CBLUE: A Chinese Biomedical LanguageUnderstanding Evaluation Benchmark
English | 中文说明 CBLUE AI (Artificial Intelligence) is playing an indispensabe role in the biomedical field, helping improve medical technology. For fur
3D AffordanceNet is a 3D point cloud benchmark consisting of 23k shapes from 23 semantic object categories, annotated with 56k affordance annotations and covering 18 visual affordance categories.
3D AffordanceNet This repository is the official experiment implementation of 3D AffordanceNet benchmark. 3D AffordanceNet is a 3D point cloud benchma
A list of hyperspectral image super-solution resources collected by Junjun Jiang
A list of hyperspectral image super-resolution resources collected by Junjun Jiang. If you find that important resources are not included, please feel free to contact me.