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cs.CV2026
Close Shortcut Wins Long: Seeking Diverse and Stable Generators for Data-Free Knowledge Distillation
Kailin Lyu, Zherui Zhang, Junhao Dong +11
Data-Free Knowledge Distillation (DFKD) preserves privacy by transferring knowledge without real data access. However, existing generator-based DFKD methods suffer from over-relian…
cs.CV2023
Generating Reliable Pixel-Level Labels for Source Free Domain Adaptation
Gabriel Tjio, Ping Liu, Yawei Luo +2
This work addresses the challenging domain adaptation setting in which knowledge from the labelled source domain dataset is available only from the pretrained black-box segmentatio…
cs.CV2023
Dual Stage Stylization Modulation for Domain Generalized Semantic Segmentation
Gabriel Tjio, Ping Liu, Chee-Keong Kwoh +1
Obtaining sufficient labeled data for training deep models is often challenging in real-life applications. To address this issue, we propose a novel solution for single-source doma…