NeurIPS 2021 - The NetHack Challenge

By AIcrowd

ASCII-rendered single-player dungeon crawl game

ADDI Alzheimers Detection Challenge

By ADDI

Machine Learning for detection of early onset of Alzheimers

Learn-to-Race: Autonomous Racing Virtual Challenge

By Carnegie Mellon University Arrival

The first, open autonomous racing challenge.

The Neural-MMO Challenge

By MIT

Robustness and teamwork in a massively multiagent environment

Seismic Facies Identification Challenge

By SEAM AI

3D Seismic Image Interpretation by Machine Learning

Insurance pricing game

By Imperial CPG

Play in a realistic insurance market, compete for profit!

Food Recognition Challenge

By Seerave Foundation

A benchmark for image-based food recognition

Dr. Derks Mutant Battlegrounds

By AIcrowd Dr Derk

Multi-agent RL in game environment. Train your Derklings, creatures with a neural network brain, to fight for you!

Learning to Smell

By Firmenich

Predicting smell of molecular compounds

CYD Campus Aircraft Localization Competition

By OpenSky Network Cyber-Defence Campus, armasuisse

Find all the aircraft!

NeurIPS 2019 : Disentanglement Challenge

By Max Planck Institute for Intelligent Systems

Disentanglement: from simulation to real-world

NeurIPS 2019 : MineRL Competition

By MineRL Labs - Carnegie Mellon University

Sample-efficient reinforcement learning in Minecraft

Flatland Challenge

By SBB

Multi Agent Reinforcement Learning on Trains.

ICCV 2019: Learning-to-Drive Challenge

By Computer Vision Lab - ETH Zurich

Immitation Learning for Autonomous Driving

Unity Obstacle Tower Challenge

By Unity Technologies

A new benchmark for Artificial Intelligence (AI) research in Reinforcement Learning

MABe Task 1: Classical Classification

By AIcrowd MABe Team

Detect Multi-Animal Behaviors from a large, hand-labeled dataset.

MABe Task 2: Annotation Style Transfer

By AIcrowd MABe Team

Adapt Behavior Detectors to capture individuals' annotation style.

MABe Task 3: Learning New Behavior

By AIcrowd MABe Team

Learn to Recognise New Behaviors from limited training examples.