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Xiangmiao Wu

2 accepted papers

2023

Hard Sample Matters a Lot in Zero-Shot Quantization

CVPR 2023poster

Zero-shot quantization (ZSQ) is promising for compressing and accelerating deep neural networks when the data for training full-precision models are inaccessible. In ZSQ, network quantization is performed using synthetic samples, thus, the performance of quantized models depends heavily on the quali…

2021

ASCNet: Self-Supervised Video Representation Learning With Appearance-Speed Consistency

ICCV 2021poster

We study self-supervised video representation learning, which is a challenging task due to 1) sufficient labels for supervision; 2) unstructured and noisy visual information. Existing methods mainly use contrastive loss with video clips as the instances and learn visual representation by discriminat…

Cited by 56PDFScholar