67 citations · 143 across the 11 of their papers we have counts for
11 papers
A Novel Dynamic Light-Section 3D Reconstruction Method for Wide-Range Sensing
Mengjuan Chen, Qing Li, Kohei Shimasaki +3
Existing galvanometer-based laser scanning systems are challenging to apply in multi-scale 3D reconstruction because of the difficulty in achieving a balance between high reconstru…
Patch-wise Mixed-Precision Quantization of Vision Transformer
Junrui Xiao, Zhikai Li, Lianwei Yang +1
As emerging hardware begins to support mixed bit-width arithmetic computation, mixed-precision quantization is widely used to reduce the complexity of neural networks. However, Vis…
BinaryViT: Towards Efficient and Accurate Binary Vision Transformers
Junrui Xiao, Zhikai Li, Lianwei Yang +1
Vision Transformers (ViTs) have emerged as the fundamental architecture for most computer vision fields, but the considerable memory and computation costs hinders their application…
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,…
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…
I-ViT: Integer-only Quantization for Efficient Vision Transformer Inference
Zhikai Li, Qingyi Gu
Vision Transformers (ViTs) have achieved state-of-the-art performance on various computer vision applications. However, these models have considerable storage and computational ove…