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20212026
most citedReducing the Covariate Shift by Mirror Samples in Cross Domain Alignment

5 citations · 5 across the 5 of their papers we have counts for

collaborators

5 papers

cs.IR2026

Recommendation as Generation: Unifying Personalized Video Generation and Recommendation at Industrial Scale

Yanhua Cheng, Bo Wang, Haotian Zhang +17

Traditional short-video recommendation systems match user interest to a fixed pool of pre-produced videos, which limits their ability to capture fine-grained and dynamic preference…

cs.CV2024

Spatiotemporal Graph Guided Multi-modal Network for Livestreaming Product Retrieval

Xiaowan Hu, Yiyi Chen, Yan Li +5

With the rapid expansion of e-commerce, more consumers have become accustomed to making purchases via livestreaming. Accurately identifying the products being sold by salespeople,…

cs.MM2024

Music Grounding by Short Video

Zijie Xin, Minquan Wang, Jingyu Liu +4

Adding proper background music helps complete a short video to be shared. Previous work tackles the task by video-to-music retrieval (V2MR), aiming to find the most suitable music…

cs.CV2024

D&M: Enriching E-commerce Videos with Sound Effects by Key Moment Detection and SFX Matching

Jingyu Liu, Minquan Wang, Ye Ma +5

Videos showcasing specific products are increasingly important for E-commerce. Key moments naturally exist as the first appearance of a specific product, presentation of its distin…

cs.CV2021★ 5 cited

Reducing the Covariate Shift by Mirror Samples in Cross Domain Alignment

Yin Zhao, Minquan Wang, Longjun Cai

Eliminating the covariate shift cross domains is one of the common methods to deal with the issue of domain shift in visual unsupervised domain adaptation. However, current alignme…