activity
20232026
most citedGenerate E-commerce Product Background by Integrating Category Commonality and Personalized Style

1 citations · 1 across the 12 of their papers we have counts for

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Showing 2026 · cs.CVShow all

5 papers · 2 filters

cs.CV2026

FedHPro: Federated Hyper-Prototype Learning via Gradient Matching

Huan Wang, Jun Shen, Haoran Li +6

Federated Learning (FL) enables collaborative training of distributed clients while protecting privacy. To enhance generalization capability in FL, prototype-based FL is in the spo…

cs.CV2026

Design Your Ad: Personalized Advertising Image and Text Generation with Unified Autoregressive Models

Yexing Xu, Wei Feng, Shen Zhang +15

Generating realistic and user-preferred advertisements is a key challenge in e-commerce. Existing approaches utilize multiple independent models driven by click-through-rate (CTR)…

cs.CV2026

KD-CVG: A Knowledge-Driven Approach for Creative Video Generation

Linkai Liu, Wei Feng, Xi Zhao +9

Creative Generation (CG) leverages generative models to automatically produce advertising content that highlights product features, and it has been a significant focus of recent re…

cs.CV2026

InnoAds-Composer: Efficient Condition Composition for E-Commerce Poster Generation

Yuxin Qin, Ke Cao, Haowei Liu +13

E-commerce product poster generation aims to automatically synthesize a single image that effectively conveys product information by presenting a subject, text, and a designed styl…

cs.CV2026

One Size, Many Fits: Aligning Diverse Group-Wise Click Preferences in Large-Scale Advertising Image Generation

Shuo Lu, Haohan Wang, Wei Feng +14

Advertising image generation has increasingly focused on online metrics like Click-Through Rate (CTR), yet existing approaches adopt a ``one-size-fits-all" strategy that optimizes…