5 citations · 7 across the 5 of their papers we have counts for
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cs.CV2025
Enhancing Generalization in Data-free Quantization via Mixup-class Prompting
Jiwoong Park, Chaeun Lee, Yongseok Choi +3
Post-training quantization (PTQ) improves efficiency but struggles with limited calibration data, especially under privacy constraints. Data-free quantization (DFQ) mitigates this…
cs.CV2022
Tech Report: One-stage Lightweight Object Detectors
Deokki Hong
This work is for designing one-stage lightweight detectors which perform well in terms of mAP and latency. With baseline models each of which targets on GPU and CPU respectively, v…
cs.CV2022★ 2 cited
It's All In the Teacher: Zero-Shot Quantization Brought Closer to the Teacher
Kanghyun Choi, Hye Yoon Lee, Deokki Hong +4
Model quantization is considered as a promising method to greatly reduce the resource requirements of deep neural networks. To deal with the performance drop induced by quantizatio…