A Metacognitive Approach to Out-of-Distribution Detection for Segmentation-Reference-Cited by-同舟云学术

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A Metacognitive Approach to Out-of-Distribution Detection for Segmentation

Published:2024-05-13 Issue: Volume:151 Page:6642-6649
ISSN:
Container-title:2024 IEEE International Conference on Robotics and Automation (ICRA)
language:
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Author:

Gummadi Meghna¹,Kent Cassandra¹,Schmeckpeper Karl¹,Eaton Eric¹

Affiliation:

1. University of Pennsylvania,Philadelphia,PA,USA

Funder

Arm

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10609961/10609862/10611287.pdf?arnumber=10611287

Reference51 articles.

1. Improving Semantic Segmentation via Video Propagation and Label Relaxation

2. Panoptic-DeepLab: A Simple, Strong, and Fast Baseline for Bottom-Up Panoptic Segmentation

3. Improving Semantic Segmentation via Decoupled Body and Edge Supervision

4. Deep High-Resolution Representation Learning for Visual Recognition

5. Identifying unknown instances for autonomous driving;Wong

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