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20232026
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cs.CV2024

MagicFace: Training-free Universal-Style Human Image Customized Synthesis

Yibin Wang, Weizhong Zhang, Cheng Jin

Current human image customization methods leverage Stable Diffusion (SD) for its rich semantic prior. However, since SD is not specifically designed for human-oriented generation,…

cs.CV2024

ELiTe: Efficient Image-to-LiDAR Knowledge Transfer for Semantic Segmentation

Zhibo Zhang, Ximing Yang, Weizhong Zhang +1

Cross-modal knowledge transfer enhances point cloud representation learning in LiDAR semantic segmentation. Despite its potential, the \textit{weak teacher challenge} arises due to…

cs.CV2024

DreamText: High Fidelity Scene Text Synthesis

Yibin Wang, Weizhong Zhang, Honghui Xu +1

Scene text synthesis involves rendering specified texts onto arbitrary images. Current methods typically formulate this task in an end-to-end manner but lack effective character-le…

cs.CV2024

Robust Fine-tuning for Pre-trained 3D Point Cloud Models

Zhibo Zhang, Ximing Yang, Weizhong Zhang +1

This paper presents a robust fine-tuning method designed for pre-trained 3D point cloud models, to enhance feature robustness in downstream fine-tuned models. We highlight the limi…

cs.CV2024

PrimeComposer: Faster Progressively Combined Diffusion for Image Composition with Attention Steering

Yibin Wang, Weizhong Zhang, Jianwei Zheng +1

Image composition involves seamlessly integrating given objects into a specific visual context. Current training-free methods rely on composing attention weights from several sampl…

cs.CV2024

Out-of-Distribution Detection using Neural Activation Prior

Weilin Wan, Weizhong Zhang, Quan Zhou +2

Out-of-distribution detection (OOD) is a crucial technique for deploying machine learning models in the real world to handle the unseen scenarios. In this paper, we first propose a…

cs.CV2023

Point Cloud Part Editing: Segmentation, Generation, Assembly, and Selection

Kaiyi Zhang, Yang Chen, Ximing Yang +2

Ideal part editing should guarantee the diversity of edited parts, the fidelity to the remaining parts, and the quality of the results. However, previous methods do not disentangle…

cs.CV2023

Enhancing Object Coherence in Layout-to-Image Synthesis

Yibin Wang, Changhai Zhou, Honghui Xu

Layout-to-image synthesis is an emerging technique in conditional image generation. It aims to generate complex scenes, where users require fine control over the layout of the obje…

cs.CV2023

High-fidelity Person-centric Subject-to-Image Synthesis

Yibin Wang, Weizhong Zhang, Jianwei Zheng +1

Current subject-driven image generation methods encounter significant challenges in person-centric image generation. The reason is that they learn the semantic scene and person gen…