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Morteza Saberi

2 accepted papers

2026

Adapt-As-You-Walk Through the Clouds: Training-Free Online Test-Time Adaptation of 3D Vision-Language Foundation Models

AAAI 2026technical

3D Vision-Language Foundation Models (VLFMs) have demonstrated strong generalization and zero-shot recognition capabilities in open-world point cloud processing tasks. However, their performance often degrades in practical scenarios where data are noisy, incomplete, or drawn from distributions that

Cited by 0SourcePDFScholar
2022

Few-Shot Class-Incremental Learning for 3D Point Cloud Objects

ECCV 2022poster

"Few-shot class-incremental learning (FSCIL) aims to incrementally fine-tune a model trained on base classes for a novel set of classes using a few examples without forgetting the previous training. Recent efforts of FSCIL addresses this problem primarily on 2D image data. However, due to the advanc…