GitHub

[ICCV 2025] D³QE: Learning Discrete Distribution Discrepancy-aware Quantization Error for Autoregressive-Generated Image Detection

Integrates dynamic codebook frequency statistics into a transformer attention module. Fuses semantic image features with latent representations of quantization ...
IEEE

BRIC: Bottom-Up Residual Vector Quantization for Learned Image Compression

Abstract: This paper presents Bottom-up Residual vector quantization for learned Image Compression (BRIC). This novel deep learning-based image compression method quantizes latent representations ...
IEEE

NLIC: Non-Uniform Quantization-Based Learned Image Compression

Abstract: In recent years, Learned Image Compression (LIC) has undergone rapid evolution. However, it is worthy noting that most prevalent LIC methodologies still rely on uniform Scalar Quantization ...
Scientific Research Publishing

Tolerance of the ERP Signatures of Unfamiliar versus Familiar Face Perception to Spatial Quantization of Facial Images ()

Processing of faces as stimuli is known to be associated with a conspicuous ERP component N170. Processing of fa-miliar faces is found to be associated with an increased amplitude of the ERP ...
GitHub

MixDQ: Memory-Efficient Few-Step Text-to-Image Diffusion Models with Metric-Decoupled Mixed Precision Quantization

This repo contains the official code of our ECCV2024 paper: MixDQ: Memory-Efficient Few-Step Text-to-Image Diffusion Models with Metric-Decoupled Mixed Precision Quantization We design MixDQ, a ...