Search Results for author: Qian He

Found 28 papers, 11 papers with code

Transforming Wearable Data into Health Insights using Large Language Model Agents

no code implementations10 Jun 2024 Mike A. Merrill, Akshay Paruchuri, Naghmeh Rezaei, Geza Kovacs, Javier Perez, Yun Liu, Erik Schenck, Nova Hammerquist, Jake Sunshine, Shyam Tailor, Kumar Ayush, Hao-Wei Su, Qian He, Cory Y. McLean, Mark Malhotra, Shwetak Patel, Jiening Zhan, Tim Althoff, Daniel McDuff, Xin Liu

Despite the proliferation of wearable health trackers and the importance of sleep and exercise to health, deriving actionable personalized insights from wearable data remains a challenge because doing so requires non-trivial open-ended analysis of these data.

Code Generation Information Retrieval +3

PuLID: Pure and Lightning ID Customization via Contrastive Alignment

1 code implementation24 Apr 2024 Zinan Guo, Yanze Wu, Zhuowei Chen, Lang Chen, Qian He

We propose Pure and Lightning ID customization (PuLID), a novel tuning-free ID customization method for text-to-image generation.

Text-to-Image Generation

DEADiff: An Efficient Stylization Diffusion Model with Disentangled Representations

1 code implementation CVPR 2024 Tianhao Qi, Shancheng Fang, Yanze Wu, Hongtao Xie, Jiawei Liu, Lang Chen, Qian He, Yongdong Zhang

The Q-Formers are trained using paired images rather than the identical target, in which the reference image and the ground-truth image are with the same style or semantics.

Disentanglement

Never-Ending Behavior-Cloning Agent for Robotic Manipulation

no code implementations1 Mar 2024 Wenqi Liang, Gan Sun, Qian He, Yu Ren, Jiahua Dong, Yang Cong

It can continually learn observation knowledge of novel 3D scene semantics and robot manipulation skills from skill-shared and skill-specific attributes, respectively.

Attribute Robot Manipulation

RealCustom: Narrowing Real Text Word for Real-Time Open-Domain Text-to-Image Customization

no code implementations CVPR 2024 Mengqi Huang, Zhendong Mao, Mingcong Liu, Qian He, Yongdong Zhang

However, the inherent entangled influence scope of pseudo-words with the given text results in a dual-optimum paradox, i. e., the similarity of the given subjects and the controllability of the given text could not be optimal simultaneously.

DreamTuner: Single Image is Enough for Subject-Driven Generation

no code implementations21 Dec 2023 Miao Hua, Jiawei Liu, Fei Ding, Wei Liu, Jie Wu, Qian He

Diffusion-based models have demonstrated impressive capabilities for text-to-image generation and are expected for personalized applications of subject-driven generation, which require the generation of customized concepts with one or a few reference images.

Text-to-Image Generation

GaFET: Learning Geometry-aware Facial Expression Translation from In-The-Wild Images

no code implementations ICCV 2023 Tianxiang Ma, Bingchuan Li, Qian He, Jing Dong, Tieniu Tan

In this paper, we introduce a novel Geometry-aware Facial Expression Translation (GaFET) framework, which is based on parametric 3D facial representations and can stably decoupled expression.

Facial Expression Translation

DreamIdentity: Improved Editability for Efficient Face-identity Preserved Image Generation

no code implementations1 Jul 2023 Zhuowei Chen, Shancheng Fang, Wei Liu, Qian He, Mengqi Huang, Yongdong Zhang, Zhendong Mao

While large-scale pre-trained text-to-image models can synthesize diverse and high-quality human-centric images, an intractable problem is how to preserve the face identity for conditioned face images.

Image Generation

Semantic 3D-aware Portrait Synthesis and Manipulation Based on Compositional Neural Radiance Field

1 code implementation3 Feb 2023 Tianxiang Ma, Bingchuan Li, Qian He, Jing Dong, Tieniu Tan

CNeRF divides the image by semantic regions and learns an independent neural radiance field for each region, and finally fuses them and renders the complete image.

ReGANIE: Rectifying GAN Inversion Errors for Accurate Real Image Editing

no code implementations31 Jan 2023 Bingchuan Li, Tianxiang Ma, Peng Zhang, Miao Hua, Wei Liu, Qian He, Zili Yi

Specifically, in Phase I, a W-space-oriented StyleGAN inversion network is trained and used to perform image inversion and editing, which assures the editability but sacrifices reconstruction quality.

Image Generation

HRTransNet: HRFormer-Driven Two-Modality Salient Object Detection

1 code implementation8 Jan 2023 Bin Tang, Zhengyi Liu, Yacheng Tan, Qian He

To solve the second problem, a dual-direction short connection fusion module is used to optimize the output features of HRFormer, thereby enhancing the detailed representation of objects at the output level.

Object object-detection +3

Part-aware Prototypical Graph Network for One-shot Skeleton-based Action Recognition

no code implementations19 Aug 2022 Tailin Chen, Desen Zhou, Jian Wang, Shidong Wang, Qian He, Chuanyang Hu, Errui Ding, Yu Guan, Xuming He

In this paper, we study the problem of one-shot skeleton-based action recognition, which poses unique challenges in learning transferable representation from base classes to novel classes, particularly for fine-grained actions.

Action Recognition Meta-Learning +1

Current and perspective sensing methods for monkeypox virus: a reemerging zoonosis in its infancy

no code implementations10 Aug 2022 Ijaz Gul, Changyue Liu, Yuan Xi, Zhicheng Du, Shiyao Zhai, Zhengyang Lei, Chen Qun, Muhammad Akmal Raheem, Qian He, Zhang Haihui, Canyang Zhang, Runming Wang, Sanyang Han, Du Ke, Peiwu Qin

Objectives The review is dedicated to evaluate the current monkeypox virus (MPXV) detection methods, discuss their pros and cons, and provide recommended solutions to the problems.

Mutual Information-guided Knowledge Transfer for Novel Class Discovery

no code implementations24 Jun 2022 Chuyu Zhang, Chuanyang Hu, Ruijie Xu, Zhitong Gao, Qian He, Xuming He

Our insight is to utilize mutual information to measure the relation between seen classes and unseen classes in a restricted label space and maximizing mutual information promotes transferring semantic knowledge.

Novel Class Discovery Relation +1

SwinNet: Swin Transformer drives edge-aware RGB-D and RGB-T salient object detection

1 code implementation12 Apr 2022 Zhengyi Liu, Yacheng Tan, Qian He, Yun Xiao

It is driven by Swin Transformer to extract the hierarchical features, boosted by attention mechanism to bridge the gap between two modalities, and guided by edge information to sharp the contour of salient object.

Decoder object-detection +2

XMP-Font: Self-Supervised Cross-Modality Pre-training for Few-Shot Font Generation

no code implementations CVPR 2022 Wei Liu, Fangyue Liu, Fei Ding, Qian He, Zili Yi

The cross-modality encoder is pre-trained in a self-supervised manner to allow effective capture of cross- and intra-modality correlations, which facilitates the content-style disentanglement and modeling style representations of all scales (stroke-level, component-level and character-level).

Disentanglement Font Generation

Region-Aware Face Swapping

no code implementations CVPR 2022 Chao Xu, Jiangning Zhang, Miao Hua, Qian He, Zili Yi, Yong liu

This paper presents a novel Region-Aware Face Swapping (RAFSwap) network to achieve identity-consistent harmonious high-resolution face generation in a local-global manner: \textbf{1)} Local Facial Region-Aware (FRA) branch augments local identity-relevant features by introducing the Transformer to effectively model misaligned cross-scale semantic interaction.

Face Generation Face Swapping +1

CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIP

2 code implementations1 Mar 2022 ZiHao Wang, Wei Liu, Qian He, Xinglong Wu, Zili Yi

Once trained, the transformer can generate coherent image tokens based on the text embedding extracted from the text encoder of CLIP upon an input text.

Text-to-Image Generation

Weakly Supervised Nuclei Segmentation via Instance Learning

1 code implementation3 Feb 2022 Weizhen Liu, Qian He, Xuming He

Weakly supervised nuclei segmentation is a critical problem for pathological image analysis and greatly benefits the community due to the significant reduction of labeling cost.

Instance Segmentation Representation Learning +2

DyStyle: Dynamic Neural Network for Multi-Attribute-Conditioned Style Editing

1 code implementation22 Sep 2021 Bingchuan Li, Shaofei Cai, Wei Liu, Peng Zhang, Qian He, Miao Hua, Zili Yi

To address these limitations, we design a Dynamic Style Manipulation Network (DyStyle) whose structure and parameters vary by input samples, to perform nonlinear and adaptive manipulation of latent codes for flexible and precise attribute control.

Attribute Contrastive Learning

FaceEraser: Removing Facial Parts for Augmented Reality

1 code implementation22 Sep 2021 Miao Hua, Lijie Liu, Ziyang Cheng, Qian He, Bingchuan Li, Zili Yi

Whereas, this technique does not satisfy the requirements of facial parts removal, as it is hard to obtain ``ground-truth'' images with real ``blank'' faces.

Image Inpainting

Single Image 3D Object Estimation with Primitive Graph Networks

1 code implementation9 Sep 2021 Qian He, Desen Zhou, Bo Wan, Xuming He

To address those challenges, we adopt a primitive-based representation for 3D object, and propose a two-stage graph network for primitive-based 3D object estimation, which consists of a sequential proposal module and a graph reasoning module.

Graph Neural Network Object +1

Weakly Supervised Volumetric Segmentation via Self-taught Shape Denoising Model

1 code implementation27 Apr 2021 Qian He, Shuailin Li, Xuming He

Moreover, we introduce a weak annotation scheme with a hybrid label design for volumetric images, which improves model learning without increasing the overall annotation cost.

Denoising Organ Segmentation +2

An Empirical Study of Propagation-based Methods for Video Object Segmentation

no code implementations30 Jul 2019 Hengkai Guo, Wenji Wang, Guanjun Guo, Huaxia Li, Jiachen Liu, Qian He, Xuefeng Xiao

While propagation-based approaches have achieved state-of-the-art performance for video object segmentation, the literature lacks a fair comparison of different methods using the same settings.

Object Semantic Segmentation +2

Reconstruction of 3-D Atomic Distortions from Electron Microscopy with Deep Learning

no code implementations19 Feb 2019 Nouamane Laanait, Qian He, Albina Y. Borisevich

Deep learning has demonstrated superb efficacy in processing imaging data, yet its suitability in solving challenging inverse problems in scientific imaging has not been fully explored.

Cannot find the paper you are looking for? You can Submit a new open access paper.