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Research map / Continual learning / Domain and prompt-based

Lifelong Person Re-identification via Knowledge Refreshing and Consolidation

AAAI 2023 · Continual learning › Domain and prompt-based · approach: Lifelong person re-identification · 38 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add knowledge refreshing to knowledge rehearsal (ablation)KRC · Averageaverage incremental R-1: 55.8 -> 70.7Helped
Add model-space and feature-space consolidation to knowledge rehearsal (ablation)KRC · Averageaverage incremental R-1: 55.8 -> 63.0Helped
Add model-space consolidation to knowledge rehearsal and refreshing (ablation)KRC · Averageaverage incremental R-1: 73.5 -> 71.8Hurt
Add feature-space consolidation to knowledge rehearsal and refreshing (ablation)KRC · Averageaverage incremental R-1: 71.8 -> 77.0Helped
Use model-space and feature-space consolidation together rather than feature-space consolidation alone (ablation)KRC · Averageaverage incremental R-1: 73.5 -> 71.8Hurt
Refresh the memory model using new-task data to support backward transferKRC · Seen-domain tasksBWT: 3.4 -> 5.3Helped
Use the refreshing-and-consolidation framework to support forward transferKRC · Seen-domain tasksFWT R-1: -13.2 -> 3.9Helped

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