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20242026
most citedDiffFAE: Advancing High-fidelity One-shot Facial Appearance Editing with Space-sensitive Customization and Semantic Preservation

1 citations · 4 across the 16 of their papers we have counts for

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Showing 2024 · cs.CVShow all

6 papers · 2 filters

cs.CV2024★ 1 cited

FitDiT: Advancing the Authentic Garment Details for High-fidelity Virtual Try-on

Boyuan Jiang, Xiaobin Hu, Donghao Luo +7

Although image-based virtual try-on has made considerable progress, emerging approaches still encounter challenges in producing high-fidelity and robust fitting images across diver…

cs.CV2024

SVP: Style-Enhanced Vivid Portrait Talking Head Diffusion Model

Weipeng Tan, Chuming Lin, Chengming Xu +5

Talking Head Generation (THG), typically driven by audio, is an important and challenging task with broad application prospects in various fields such as digital humans, film produ…

cs.CV2024

CustAny: Customizing Anything from A Single Example

Lingjie Kong, Kai Wu, Xiaobin Hu +8

Recent advances in diffusion-based text-to-image models have simplified creating high-fidelity images, but preserving the identity (ID) of specific elements, like a personal dog, i…

cs.CV2024★ 1 cited

VividPose: Advancing Stable Video Diffusion for Realistic Human Image Animation

Qilin Wang, Zhengkai Jiang, Chengming Xu +7

Human image animation involves generating a video from a static image by following a specified pose sequence. Current approaches typically adopt a multi-stage pipeline that separat…

cs.CV2024★ 1 cited

Towards Global Optimal Visual In-Context Learning Prompt Selection

Chengming Xu, Chen Liu, Yikai Wang +2

Visual In-Context Learning (VICL) is a prevailing way to transfer visual foundation models to new tasks by leveraging contextual information contained in in-context examples to enh…

cs.CV2024★ 1 cited

DiffFAE: Advancing High-fidelity One-shot Facial Appearance Editing with Space-sensitive Customization and Semantic Preservation

Qilin Wang, Jiangning Zhang, Chengming Xu +7

Facial Appearance Editing (FAE) aims to modify physical attributes, such as pose, expression and lighting, of human facial images while preserving attributes like identity and back…