SegQuant: A Semantics-Aware and Generalizable Quantization Framework for Diffusion Models

arXiv:2507.14811 · cs.CV, cs.AI · Submitted 2025-07-20 · Read on arXiv

cs.CV, cs.AI

Submitted: 2025-07-20

Updated: 2026-03-15

Comments: 22 pages, 15 figures, to be published in The IEEE/CVF Conference on Computer Vision and Pattern Recognition 2026 (CVPR 2026), code is available at https://github.com/OptiSys-ZJU/segquant

Journal ref: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2026, pp. 43717-43726

Code: https://github.com/OptiSys-ZJU/segquant

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

Quantization — 144× in this paper · explained in 12 episodes
Diffusion Model — 36× in this paper · explained in 8 episodes
Diffusion Models — 34× in this paper · explained in 6 episodes
Transformer — 17× in this paper · explained in 2 episodes
Calibration — 14× in this paper · explained in 7 episodes
Fidelity — 13× in this paper · explained in 2 episodes
Alignment — 7× in this paper · explained in 1 episode
Ablation — 6× in this paper · explained in 1 episode
Accuracy — 4× in this paper · explained in 1 episode
Core — 4× in this paper · explained in 2 episodes
Semantic Alignment — 4× in this paper · explained in 3 episodes
Activation Function — 3× in this paper · explained in 1 episode
Adam — 3× in this paper · explained in 2 episodes
Consistency — 3× in this paper · explained in 3 episodes
Embeddings — 3× in this paper · explained in 2 episodes
Rectified Flow — 3× in this paper · explained in 3 episodes
Ablation study — 2× in this paper · explained in 1 episode
Abstraction — 2× in this paper · explained in 1 episode
Fine-Tuning — 2× in this paper · explained in 5 episodes
Flow Matching — 2× in this paper · explained in 8 episodes
Generalizability — 2× in this paper · explained in 6 episodes
Generative Model — 2× in this paper · explained in 2 episodes
Generative Models — 2× in this paper · explained in 2 episodes
International Conference on Computer Vision — 2× in this paper
Mean Squared Error — 2× in this paper
Robustness — 2× in this paper · explained in 5 episodes
Trace — 2× in this paper · explained in 2 episodes
Adaptation — 1× in this paper · explained in 1 episode
Aggregation — 1× in this paper · explained in 1 episode
Aperture — 1× in this paper · explained in 1 episode
Benchmark — 1× in this paper · explained in 2 episodes
Cosine Similarity — 1× in this paper · explained in 3 episodes
Distillation — 1× in this paper · explained in 2 episodes
Elias — 1× in this paper · explained in 2 episodes
Generalization — 1× in this paper · explained in 13 episodes
Generative Modeling — 1× in this paper · explained in 3 episodes
Iterative Refinement — 1× in this paper · explained in 3 episodes
Latent Diffusion Model — 1× in this paper · explained in 2 episodes
Latent Diffusion Models — 1× in this paper · explained in 2 episodes
Learned Perceptual Image Patch Similarity — 1× in this paper
Model-Agnostic — 1× in this paper · explained in 2 episodes
Nash Equilibrium — 1× in this paper · explained in 2 episodes
Peak Signal-to-Noise Ratio — 1× in this paper
Quantization-Aware Training — 1× in this paper · explained in 3 episodes
Reconstruction Error — 1× in this paper · explained in 2 episodes
Singular Value Decomposition (SVD) — 1× in this paper · explained in 2 episodes
Sparsity — 1× in this paper · explained in 4 episodes
Structural Similarity Index Measure — 1× in this paper
Transformer Architecture — 1× in this paper · explained in 2 episodes
Variational Autoencoder (VAE) — 1× in this paper · explained in 3 episodes
Variational Bayes — 1× in this paper · explained in 2 episodes

Terminology

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