XiaohanLei / IEVE

PyTorch implementation of CVPR 2024 paper: Instance-aware Exploration-Verification-Exploitation for Instance ImageGoal Navigation
https://xiaohanlei.github.io/projects/IEVE/
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[CVPR 2024] Instance-aware Exploration-Verification-Exploitation for Instance ImageGoal Navigation

This is the pytorch implementation of CVPR 2024 paper: Instance-aware Exploration-Verification-Exploitation for Instance ImageGoal Navigation (IEVE).

Now the action space aligns with the paper reported (velocity control). If you have any other issues, feel free to contact us!

Project Page

example

Overview:

Inspired by the human behavior of “getting closer to confirm” when recognizing distant objects, we formulate the task of determining whether an object matches the one in the goal image as a sequential decision problem. In addition, we design a novel matching function that relies not only on the current observation and goal image but also on the Euclidean distance between the agent and the potential target. We categorize the targets into confirmed target, potential target, and no-target (exploration), and allow the agent to actively choose among these three targets.

Installing Dependencies

Downloading scene dataset and episode dataset

Pretrained models

Test setup

To test in the val set, run:

python main.py

Some tips

Bibtex:

@inproceedings{lei2024instance,
  title={Instance-aware Exploration-Verification-Exploitation for Instance ImageGoal Navigation},
  author={Lei, Xiaohan and Wang, Min and Zhou, Wengang and Li, Li and Li, Houqiang},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={16329--16339},
  year={2024}
}