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Doodle to Object: Practical Zero-Shot Sketch-Based 3D Shape Retrieval

AAAI 2023 · Label-efficient and robust learning › Zero-/few-shot and meta-learning · approach: Transductive and semantic-dictionary zero-shot · 6 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
use PCL instead of CGNZS-SBSR retrieval · SHREC’13mAP: 38.6 -> 48.0Helped
use PCL instead of CGNZS-SBSR retrieval · SHREC’14mAP: 35.6 -> 43.4Helped
use PCL instead of CGNZS-SBSR retrieval · D2OmAP: 25.0 -> 29.9Helped
add cross-domain feature alignment (ablation)PCL · SHREC’13 ZS-SBSRmAP: 23.2 -> 48.0Helped
add cross-domain feature alignment (ablation)PCL · SHREC’14 ZS-SBSRmAP: 24.1 -> 43.4Helped
add cross-domain feature alignment (ablation)PCL · D2O ZS-SBSRmAP: 16.5 -> 29.9Helped
combine prototype and contrastive learning rather than use dynamic clustering (ablation)cross-domain aligned retrieval · SHREC’13 ZS-SBSRmAP: 34.7 -> 48.0Helped
combine prototype and contrastive learning rather than use fixed anchor points (ablation)cross-domain aligned retrieval · SHREC’14 ZS-SBSRmAP: 30.3 -> 43.4Helped
use 80% stroke accumulation with the RNN rather than only the final sketch image (ablation)D2O retrieval · SBSRmAP: 51.3 -> 50.8No clear effect
use 100% stroke accumulation with the RNN rather than only the final sketch image (ablation)D2O retrieval · ZS-SBSRmAP: 29.9 -> 30.4No clear effect

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