HiVT

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HiVT is an Open Source & Models tool that provides a hierarchical vector transformer for multi-agent motion prediction. It offers pretrained models and training scripts for autonomous driving applications.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Skill level

Technical

About

What is HiVT?

HiVT (Hierarchical Vector Transformer) is an open-source implementation of a multi-agent motion prediction model, published in CVPR 2022. This repository provides the official code for training and evaluating the HiVT model, which is designed to predict the future movements of multiple agents in complex environments, such as those encountered in autonomous driving. Users can leverage pretrained models (HiVT-64 and HiVT-128) or train their own using the provided scripts and the Argoverse Motion Forecasting Dataset. The project includes detailed instructions for setup, data preparation, training, and evaluation, making it a valuable resource for researchers and developers in the field of autonomous systems.

Best used for

Ideal for developers and data scientists who need to implement advanced multi-agent motion prediction models, train custom AI models for trajectory forecasting, and evaluate performance on standard datasets. Especially valuable for those working on autonomous driving and robotics applications.

Common actions

predict motion

train AI models

implement transformers

analyze trajectories

github copilot"AI Agents"face swappinglow-code/no-codedeepfakeopen-sourceautomated workflowcollaborationworkflows

Capabilities

Key features

Hierarchical vector transformer
Multi-agent motion prediction
Pretrained models available
Training scripts provided
Argoverse dataset integration
CVPR 2022 publication

Target Audience

developerdata scientist

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What kind of motion prediction does HiVT specialize in?

HiVT specializes in multi-agent motion prediction, meaning it can predict the movements of multiple entities simultaneously within a given environment. This is particularly useful for complex scenarios like autonomous driving where interactions between various agents (vehicles, pedestrians) are crucial.

What dataset is recommended for training HiVT?

The HiVT repository recommends using the Argoverse Motion Forecasting Dataset v1.1 for training and evaluation. Instructions are provided on how to download, extract, and organize this dataset to be compatible with the HiVT training scripts.

Are there any pretrained models available for HiVT?

Yes, the HiVT repository provides pretrained models for both HiVT-64 and HiVT-128 configurations. These can be used directly for evaluation or as a starting point for further fine-tuning, saving significant training time.

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