52 citations · 59 across the 7 of their papers we have counts for
Showing 2022Show all
3 papers · 1 filter
cs.CV2022★ 4 cited
RepQ-ViT: Scale Reparameterization for Post-Training Quantization of Vision Transformers
Zhikai Li, Junrui Xiao, Lianwei Yang +1
Post-training quantization (PTQ), which only requires a tiny dataset for calibration without end-to-end retraining, is a light and practical model compression technique. Recently,…
cs.CV2022★ 2 cited
PSAQ-ViT V2: Towards Accurate and General Data-Free Quantization for Vision Transformers
Zhikai Li, Mengjuan Chen, Junrui Xiao +1
Data-free quantization can potentially address data privacy and security concerns in model compression, and thus has been widely investigated. Recently, PSAQ-ViT designs a relative…
cs.CV2022★ 52 cited
Patch Similarity Aware Data-Free Quantization for Vision Transformers
Zhikai Li, Liping Ma, Mengjuan Chen +2
Vision transformers have recently gained great success on various computer vision tasks; nevertheless, their high model complexity makes it challenging to deploy on resource-constr…