Search Results for author: Hanhui Li

Found 11 papers, 6 papers with code

AutoStudio: Crafting Consistent Subjects in Multi-turn Interactive Image Generation

1 code implementation3 Jun 2024 Junhao Cheng, Xi Lu, Hanhui Li, Khun Loun Zai, Baiqiao Yin, Yuhao Cheng, Yiqiang Yan, Xiaodan Liang

As cutting-edge Text-to-Image (T2I) generation models already excel at producing remarkable single images, an even more challenging task, i. e., multi-turn interactive image generation begins to attract the attention of related research communities.

Image Generation

TheaterGen: Character Management with LLM for Consistent Multi-turn Image Generation

1 code implementation29 Apr 2024 Junhao Cheng, Baiqiao Yin, Kaixin Cai, Minbin Huang, Hanhui Li, Yuxin He, Xi Lu, Yue Li, Yifei Li, Yuhao Cheng, Yiqiang Yan, Xiaodan Liang

To address this issue, we introduce TheaterGen, a training-free framework that integrates large language models (LLMs) and text-to-image (T2I) models to provide the capability of multi-turn image generation.

Denoising Image Generation +2

ConsistentID: Portrait Generation with Multimodal Fine-Grained Identity Preserving

1 code implementation25 Apr 2024 Jiehui Huang, Xiao Dong, Wenhui Song, Hanhui Li, Jun Zhou, Yuhao Cheng, Shutao Liao, Long Chen, Yiqiang Yan, Shengcai Liao, Xiaodan Liang

ConsistentID comprises two key components: a multimodal facial prompt generator that combines facial features, corresponding facial descriptions and the overall facial context to enhance precision in facial details, and an ID-preservation network optimized through the facial attention localization strategy, aimed at preserving ID consistency in facial regions.

3D Visibility-aware Generalizable Neural Radiance Fields for Interacting Hands

1 code implementation2 Jan 2024 Xuan Huang, Hanhui Li, Zejun Yang, Zhisheng Wang, Xiaodan Liang

Subsequently, a feature fusion module that exploits the visibility of query points and mesh vertices is introduced to adaptively merge features of both hands, enabling the recovery of features in unseen areas.

Monocular 3D Hand Mesh Recovery via Dual Noise Estimation

1 code implementation26 Dec 2023 Hanhui Li, Xiaojian Lin, Xuan Huang, Zejun Yang, Zhisheng Wang, Xiaodan Liang

However, due to the fixed hand topology and complex hand poses, current models are hard to generate meshes that are aligned with the image well.

Noise Estimation

Towards Hard-pose Virtual Try-on via 3D-aware Global Correspondence Learning

1 code implementation25 Nov 2022 Zaiyu Huang, Hanhui Li, Zhenyu Xie, Michael Kampffmeyer, Qingling Cai, Xiaodan Liang

Existing methods are restricted in this setting as they estimate garment warping flows mainly based on 2D poses and appearance, which omits the geometric prior of the 3D human body shape.

Virtual Try-on

BodyGAN: General-Purpose Controllable Neural Human Body Generation

no code implementations CVPR 2022 Chaojie Yang, Hanhui Li, Shengjie Wu, Shengkai Zhang, Haonan Yan, Nianhong Jiao, Jie Tang, Runnan Zhou, Xiaodan Liang, Tianxiang Zheng

This is because current methods mainly rely on a single pose/appearance model, which is limited in disentangling various poses and appearance in human images.

Disentanglement Image Generation +1

Multi-column Point-CNN for Sketch Segmentation

no code implementations28 Dec 2018 Fei Wang, Shujin Lin, Hanhui Li, Hefeng Wu, Junkun Jiang, Ruomei Wang, Xiaonan Luo

Traditional sketch segmentation methods mainly rely on handcrafted features and complicate models, and their performance is far from satisfactory due to the abstract representation of sketches.

Beyond Context: Exploring Semantic Similarity for Tiny Face Detection

no code implementations5 Mar 2018 Yue Xi, Jiangbin Zheng, Xiangjian He, Wenjing Jia, Hanhui Li

Tiny face detection aims to find faces with high degrees of variability in scale, resolution and occlusion in cluttered scenes.

Face Detection Metric Learning +2

Structured Inhomogeneous Density Map Learning for Crowd Counting

no code implementations20 Jan 2018 Hanhui Li, Xiangjian He, Hefeng Wu, Saeed Amirgholipour Kasmani, Ruomei Wang, Xiaonan Luo, Liang Lin

In this paper, we aim at tackling the problem of crowd counting in extremely high-density scenes, which contain hundreds, or even thousands of people.

Crowd Counting

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