Baisen Wang — accepted AI-conference papers

2026

Z-Erase: Enabling Concept Erasure in Single Stream Diffusion Transformers

Nanxiang Jiang, Zhaoxin Fan, Baisen Wang, Daiheng Gao, Junhang Cheng, Jifeng Guo +5

ICML 2026poster

Concept erasure serves as a vital safety mechanism for removing unwanted concepts from text-to-image (T2I) models. While extensively studied in U-Net and dual-stream architectures (e.g., Flux), this task remains under-explored in the recent emerging paradigm of single-stream diffusion transformers (…

Cited by 0 Source ↗Scholar ↗

2023

Video Background Music Generation: Dataset, Method and Evaluation

Le Zhuo, Zhaokai Wang, Baisen Wang, Yue Liao, Chenxi Bao, Stanley Peng +4

ICCV 2023poster

Music is essential when editing videos, but selecting music manually is difficult and time-consuming. Thus, we seek to automatically generate background music tracks given video input. This is a challenging task since it requires music-video datasets, efficient architectures for video-to-music gener…

Cited by 38 PDF ↗code ↗Scholar ↗