Debin Meng — accepted AI-conference papers

2026

Diffusion-Based Makeup Transfer with Facial Region-Aware Makeup Features

Zheng Gao, Debin Meng, Yunqi Miao, Zhensong Zhang, Songcen Xu, Ioannis Patras +1

CVPR 2026

Current diffusion-based makeup transfer methods commonly use the makeup information encoded by off-the-shelf foundation models (e.g., CLIP) as condition to preserve the makeup style of reference image in the generation. Although effective, these works mainly have two limitations: (1) foundation mode

Cited by 0 Source ↗code ↗Scholar ↗

2021

Shallow Bayesian Meta Learning for Real-World Few-Shot Recognition

Xueting Zhang, Debin Meng, Henry Gouk, Timothy M. Hospedales

ICCV 2021poster

Many state-of-the-art few-shot learners focus on developing effective training procedures for feature representations, before using simple (e.g., nearest centroid) classifiers. We take an approach that is agnostic to the features used, and focus exclusively on meta-learning the final classifier laye…

Cited by 90 PDF ↗code ↗Scholar ↗