Search Results for author: Yu Deng

Found 29 papers, 10 papers with code

Portrait4D-v2: Pseudo Multi-View Data Creates Better 4D Head Synthesizer

no code implementations20 Mar 2024 Yu Deng, Duomin Wang, Baoyuan Wang

In this paper, we propose a novel learning approach for feed-forward one-shot 4D head avatar synthesis.

Deep learning with noisy labels in medical prediction problems: a scoping review

no code implementations19 Mar 2024 Yishu Wei, Yu Deng, Cong Sun, Mingquan Lin, Hongmei Jiang, Yifan Peng

This scoping review aims to comprehensively review label noise management in deep learning-based medical prediction problems, which includes label noise detection, label noise handling, and evaluation.

Learning with noisy labels Management

Seed-Guided Fine-Grained Entity Typing in Science and Engineering Domains

1 code implementation23 Jan 2024 Yu Zhang, Yunyi Zhang, Yanzhen Shen, Yu Deng, Lucian Popa, Larisa Shwartz, ChengXiang Zhai, Jiawei Han

In this paper, we study the task of seed-guided fine-grained entity typing in science and engineering domains, which takes the name and a few seed entities for each entity type as the only supervision and aims to classify new entity mentions into both seen and unseen types (i. e., those without seed entities).

Entity Typing Natural Language Inference

Learning One-Shot 4D Head Avatar Synthesis using Synthetic Data

no code implementations30 Nov 2023 Yu Deng, Duomin Wang, Xiaohang Ren, Xingyu Chen, Baoyuan Wang

The key is to first learn a part-wise 4D generative model from monocular images via adversarial learning, to synthesize multi-view images of diverse identities and full motions as training data; then leverage a transformer-based animatable triplane reconstructor to learn 4D head reconstruction using the synthetic data.

3D Reconstruction

AgentAvatar: Disentangling Planning, Driving and Rendering for Photorealistic Avatar Agents

no code implementations29 Nov 2023 Duomin Wang, Bin Dai, Yu Deng, Baoyuan Wang

In this study, our goal is to create interactive avatar agents that can autonomously plan and animate nuanced facial movements realistically, from both visual and behavioral perspectives.

Neural Rendering

UniQuadric: A SLAM Backend for Unknown Rigid Object 3D Tracking and Light-Weight Modeling

no code implementations29 Sep 2023 Linghao Yang, Yanmin Wu, Yu Deng, Rui Tian, Xinggang Hu, Tiefeng Ma

Subsequently, in the part of object state estimation, we propose a tightly coupled optimization model for object pose and scale estimation, incorporating hybrids constraints into a novel dual sliding window optimization framework for joint estimation.

Motion Estimation Object +2

Mimic3D: Thriving 3D-Aware GANs via 3D-to-2D Imitation

no code implementations ICCV 2023 Xingyu Chen, Yu Deng, Baoyuan Wang

Improving the photorealism via CNN-based 2D super-resolution can break the strict 3D consistency, while keeping the 3D consistency by learning high-resolution 3D representations for direct rendering often compromises image quality.

Image Generation Representation Learning +1

Entity Set Co-Expansion in StackOverflow

no code implementations5 Dec 2022 Yu Zhang, Yunyi Zhang, Yucheng Jiang, Martin Michalski, Yu Deng, Lucian Popa, ChengXiang Zhai, Jiawei Han

Given a few seed entities of a certain type (e. g., Software or Programming Language), entity set expansion aims to discover an extensive set of entities that share the same type as the seeds.

graph construction Management

Progressive Disentangled Representation Learning for Fine-Grained Controllable Talking Head Synthesis

1 code implementation CVPR 2023 Duomin Wang, Yu Deng, Zixin Yin, Heung-Yeung Shum, Baoyuan Wang

We present a novel one-shot talking head synthesis method that achieves disentangled and fine-grained control over lip motion, eye gaze&blink, head pose, and emotional expression.

Contrastive Learning Disentanglement

Learning Detailed Radiance Manifolds for High-Fidelity and 3D-Consistent Portrait Synthesis from Monocular Image

no code implementations CVPR 2023 Yu Deng, Baoyuan Wang, Heung-Yeung Shum

We introduce a novel detail manifolds reconstructor to learn 3D-consistent fine details on the radiance manifolds from monocular images, and combine them with the coarse radiance manifolds for high-fidelity reconstruction.

Image Generation Novel View Synthesis

AniFaceGAN: Animatable 3D-Aware Face Image Generation for Video Avatars

1 code implementation12 Oct 2022 Yue Wu, Yu Deng, Jiaolong Yang, Fangyun Wei, Qifeng Chen, Xin Tong

To achieve meaningful control over facial expressions via deformation, we propose a 3D-level imitative learning scheme between the generator and a parametric 3D face model during adversarial training of the 3D-aware GAN.

Disentanglement Face Model +1

Generative Deformable Radiance Fields for Disentangled Image Synthesis of Topology-Varying Objects

no code implementations9 Sep 2022 Ziyu Wang, Yu Deng, Jiaolong Yang, Jingyi Yu, Xin Tong

Experiments show that our method can successfully learn the generative model from unstructured monocular images and well disentangle the shape and appearance for objects (e. g., chairs) with large topological variance.

Disentanglement Image Generation +1

GRAM-HD: 3D-Consistent Image Generation at High Resolution with Generative Radiance Manifolds

no code implementations ICCV 2023 Jianfeng Xiang, Jiaolong Yang, Yu Deng, Xin Tong

This paper proposes a novel 3D-aware GAN that can generate high resolution images (up to 1024X1024) while keeping strict 3D consistency as in volume rendering.

Image Generation Super-Resolution

Deep Learning in Human Activity Recognition with Wearable Sensors: A Review on Advances

no code implementations31 Oct 2021 Shibo Zhang, Yaxuan Li, Shen Zhang, Farzad Shahabi, Stephen Xia, Yu Deng, Nabil Alshurafa

Mobile and wearable devices have enabled numerous applications, including activity tracking, wellness monitoring, and human--computer interaction, that measure and improve our daily lives.

Human Activity Recognition

BERTSurv: BERT-Based Survival Models for Predicting Outcomes of Trauma Patients

no code implementations19 Mar 2021 Yun Zhao, Qinghang Hong, Xinlu Zhang, Yu Deng, Yuqing Wang, Linda Petzold

However, there is a lack of deep learning methods that can model the relationship between measurements, clinical notes and mortality outcomes.

Mortality Prediction Survival Analysis

A Deep Learning-Based Approach to Extracting Periosteal and Endosteal Contours of Proximal Femur in Quantitative CT Images

no code implementations3 Feb 2021 Yu Deng, Ling Wang, Chen Zhao, Shaojie Tang, Xiaoguang Cheng, Hong-Wen Deng, Weihua Zhou

In this study, we proposed an approach based on deep learning for the automatic extraction of the periosteal and endosteal contours of proximal femur in order to differentiate cortical and trabecular bone compartments.

Interactive Segmentation Segmentation

Spread Mechanism and Influence Measurement of Online Rumors in China During the COVID-19 Pandemic

no code implementations4 Dec 2020 Yiou Lin, Hang Lei, Yu Deng

The search frequency of the rumor is used as an observation variable of new insiders.

Deformed Implicit Field: Modeling 3D Shapes with Learned Dense Correspondence

1 code implementation CVPR 2021 Yu Deng, Jiaolong Yang, Xin Tong

We propose a novel Deformed Implicit Field (DIF) representation for modeling 3D shapes of a category and generating dense correspondences among shapes.

Technical Question Answering across Tasks and Domains

1 code implementation NAACL 2021 Wenhao Yu, Lingfei Wu, Yu Deng, Qingkai Zeng, Ruchi Mahindru, Sinem Guven, Meng Jiang

In this paper, we propose a novel framework of deep transfer learning to effectively address technical QA across tasks and domains.

Question Answering Reading Comprehension +2

Crossing Variational Autoencoders for Answer Retrieval

no code implementations ACL 2020 Wenhao Yu, Lingfei Wu, Qingkai Zeng, Shu Tao, Yu Deng, Meng Jiang

Existing methods learned semantic representations with dual encoders or dual variational auto-encoders.

Retrieval

Deep 3D Portrait from a Single Image

1 code implementation CVPR 2020 Sicheng Xu, Jiaolong Yang, Dong Chen, Fang Wen, Yu Deng, Yunde Jia, Xin Tong

We evaluate the accuracy of our method both in 3D and with pose manipulation tasks on 2D images.

Face Model Stereo Matching

Evaluating the Portability of an NLP System for Processing Echocardiograms: A Retrospective, Multi-site Observational Study

no code implementations2 Apr 2019 Prakash Adekkanattu, Guoqian Jiang, Yuan Luo, Paul R. Kingsbury, Zhen-Xing Xu, Luke V. Rasmussen, Jennifer A. Pacheco, Richard C. Kiefer, Daniel J. Stone, Pascal S. Brandt, Liang Yao, Yizhen Zhong, Yu Deng, Fei Wang, Jessica S. Ancker, Thomas R. Campion, Jyotishman Pathak

While the NLP system showed high precision and recall measurements for four target concepts (aortic valve regurgitation, left atrium size at end systole, mitral valve regurgitation, tricuspid valve regurgitation) across all sites, we found moderate or poor results for the remaining concepts and the NLP system performance varied between individual sites.

Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set

4 code implementations20 Mar 2019 Yu Deng, Jiaolong Yang, Sicheng Xu, Dong Chen, Yunde Jia, Xin Tong

Recently, deep learning based 3D face reconstruction methods have shown promising results in both quality and efficiency. However, training deep neural networks typically requires a large volume of data, whereas face images with ground-truth 3D face shapes are scarce.

Ranked #3 on 3D Face Reconstruction on Florence (RMSE Cooperative metric)

3D Face Reconstruction Weakly-supervised Learning

Natural Language Processing for EHR-Based Computational Phenotyping

no code implementations13 Jun 2018 Zexian Zeng, Yu Deng, Xiaoyu Li, Tristan Naumann, Yuan Luo

This article reviews recent advances in applying natural language processing (NLP) to Electronic Health Records (EHRs) for computational phenotyping.

Computational Phenotyping

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