UPDA: Unsupervised Progressive Domain Adaptation for No-Reference Point Cloud Quality Assessment

TL;DR

This paper introduces UPDA, an unsupervised progressive domain adaptation framework for no-reference point cloud quality assessment, which effectively reduces domain gaps and improves cross-domain performance through a two-stage alignment process.

Contribution

The paper presents the first unsupervised progressive domain adaptation method for NR-PCQA, utilizing a two-stage coarse-to-fine alignment to address domain shifts.

Findings

Significant performance improvement in cross-domain NR-PCQA tasks.

Effective domain-invariant feature extraction through the proposed alignment methods.

Validated on extensive experiments demonstrating practical applicability.

Abstract

While no-reference point cloud quality assessment (NR-PCQA) approaches have achieved significant progress over the past decade, their performance often degrades substantially when a distribution gap exists between the training (source domain) and testing (target domain) data. However, to date, limited attention has been paid to transferring NR-PCQA models across domains. To address this challenge, we propose the first unsupervised progressive domain adaptation (UPDA) framework for NR-PCQA, which introduces a two-stage coarse-to-fine alignment paradigm to address domain shifts. At the coarse-grained stage, a discrepancy-aware coarse-grained alignment method is designed to capture relative quality relationships between cross-domain samples through a novel quality-discrepancy-aware hybrid loss, circumventing the challenges of direct absolute feature alignment. At the fine-grained stage, a perception fusion fine-grained alignment approach with symmetric feature fusion is developed to identify domain-invariant features, while a conditional discriminator selectively enhances the transfer of quality-relevant features. Extensive experiments demonstrate that the proposed UPDA effectively enhances the performance of NR-PCQA methods in cross-domain scenarios, validating its practical applicability. The code is available at https://github.com/yokeno1/UPDA-main.