most citedGANHead: Towards Generative Animatable Neural Head Avatars

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cs.CV2025

EvoMakeup: High-Fidelity and Controllable Makeup Editing with MakeupQuad

Huadong Wu, Yi Fu, Yunhao Li +2

Facial makeup editing aims to realistically transfer makeup from a reference to a target face. Existing methods often produce low-quality results with coarse makeup details and str…

cs.CV2025

AGHI-QA: A Subjective-Aligned Dataset and Metric for AI-Generated Human Images

Yunhao Li, Sijing Wu, Wei Sun +6

The rapid development of text-to-image (T2I) generation approaches has attracted extensive interest in evaluating the quality of generated images, leading to the development of var…

cs.CV20241 cited

DiffStega: Towards Universal Training-Free Coverless Image Steganography with Diffusion Models

Yiwei Yang, Zheyuan Liu, Jun Jia +5

Traditional image steganography focuses on concealing one image within another, aiming to avoid steganalysis by unauthorized entities. Coverless image steganography (CIS) enhances…

cs.CV20241 cited

LaMOT: Language-Guided Multi-Object Tracking

Yunhao Li, Xiaoqiong Liu, Luke Liu +2

Vision-Language MOT is a crucial tracking problem and has drawn increasing attention recently. It aims to track objects based on human language commands, replacing the traditional…

cs.CV2024

DerainNeRF: 3D Scene Estimation with Adhesive Waterdrop Removal

Yunhao Li, Jing Wu, Lingzhe Zhao +1

When capturing images through the glass during rainy or snowy weather conditions, the resulting images often contain waterdrops adhered on the glass surface, and these waterdrops s…

cs.CV20231 cited

AttMOT: Improving Multiple-Object Tracking by Introducing Auxiliary Pedestrian Attributes

Yunhao Li, Zhen Xiao, Lin Yang +4

Multi-object tracking (MOT) is a fundamental problem in computer vision with numerous applications, such as intelligent surveillance and automated driving. Despite the significant…