2 papers
cs.CV2025
FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation
Zhuguanyu Wu, Shihe Wang, Jiayi Zhang +2
Post-training quantization (PTQ) has stood out as a cost-effective and promising model compression paradigm in recent years, as it avoids computationally intensive model retraining…
cs.CV2025
APHQ-ViT: Post-Training Quantization with Average Perturbation Hessian Based Reconstruction for Vision Transformers
Zhuguanyu Wu, Jiayi Zhang, Jiaxin Chen +3
Vision Transformers (ViTs) have become one of the most commonly used backbones for vision tasks. Despite their remarkable performance, they often suffer significant accuracy drops…