5 papers
Anisotropic Pooling for LUT-realizable CNN Image Restoration
Xi Zhang, Xiaolin Wu
Table look-up realization of image restoration CNNs has the potential of achieving competitive image quality while being much faster and resource frugal than the straightforward CN…
Receptive Field Expanded Look-Up Tables for Vision Inference: Advancing from Low-level to High-level Tasks
Xi Zhang, Xiaolin Wu
Recently, several look-up table (LUT) methods were developed to greatly expedite the inference of CNNs in a classical strategy of trading space for speed. However, these LUT method…
Class-Invariant Test-Time Augmentation for Domain Generalization
Zhicheng Lin, Xiaolin Wu, Xi Zhang
Deep models often suffer significant performance degradation under distribution shifts. Domain generalization (DG) seeks to mitigate this challenge by enabling models to generalize…
Learning Grouped Lattice Vector Quantizers for Low-Bit LLM Compression
Xi Zhang, Xiaolin Wu, Jiamang Wang +1
Large Language Models (LLMs) have demonstrated remarkable capabilities but typically require extensive computational resources and memory for inference. Post-training quantization…
Learning Optimal Lattice Vector Quantizers for End-to-end Neural Image Compression
Xi Zhang, Xiaolin Wu
It is customary to deploy uniform scalar quantization in the end-to-end optimized Neural image compression methods, instead of more powerful vector quantization, due to the high co…