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20242026
most citedAn Overview of the JPEG AI Learning-Based Image Coding Standard

5 citations · 6 across the 7 of their papers we have counts for

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cs.CV2025

PairHuman: A High-Fidelity Photographic Dataset for Customized Dual-Person Generation

Ting Pan, Ye Wang, Peiguang Jing +3

Personalized dual-person portrait customization has considerable potential applications, such as preserving emotional memories and facilitating wedding photography planning. Howeve…

cs.CV2025

FreeControl: Efficient, Training-Free Structural Control via One-Step Attention Extraction

Jiang Lin, Xinyu Chen, Song Wu +7

Controlling the spatial and semantic structure of diffusion-generated images remains a challenge. Existing methods like ControlNet rely on handcrafted condition maps and retraining…

eess.IV2025★ 5 cited

An Overview of the JPEG AI Learning-Based Image Coding Standard

Semih Esenlik, Yaojun Wu, Zhaobin Zhang +5

JPEG AI is an emerging learning-based image coding standard developed by Joint Photographic Experts Group (JPEG). The scope of the JPEG AI is the creation of a practical learning-b…

cs.GR2025

DP-Adapter: Dual-Pathway Adapter for Boosting Fidelity and Text Consistency in Customizable Human Image Generation

Ye Wang, Xuping Xie, Lanjun Wang +2

With the growing popularity of personalized human content creation and sharing, there is a rising demand for advanced techniques in customized human image generation. However, curr…

cs.GR2025

SigStyle: Signature Style Transfer via Personalized Text-to-Image Models

Ye Wang, Tongyuan Bai, Xuping Xie +3

Style transfer enables the seamless integration of artistic styles from a style image into a content image, resulting in visually striking and aesthetically enriched outputs. Despi…