1 code implementation • ECCV 2020 • Zehao Yu, Lei Jin, Shenghua Gao
The task is extremely challenging because of the vast areas of non-texture regions in these scenes.
no code implementations • CVPR 2024 • Lei LI, Songyou Peng, Zehao Yu, Shaohui Liu, Rémi Pautrat, Xiaochuan Yin, Marc Pollefeys
Real-world objects and environments are predominantly composed of edge features, including straight lines and curves.
1 code implementation • 16 Apr 2024 • Zehao Yu, Torsten Sattler, Andreas Geiger
Recently, 3D Gaussian Splatting (3DGS) has demonstrated impressive novel view synthesis results, while allowing the rendering of high-resolution images in real-time.
1 code implementation • 26 Mar 2024 • Binbin Huang, Zehao Yu, Anpei Chen, Andreas Geiger, Shenghua Gao
3D Gaussian Splatting (3DGS) has recently revolutionized radiance field reconstruction, achieving high quality novel view synthesis and fast rendering speed without baking.
no code implementations • 19 Mar 2024 • Cheng Peng, Zehao Yu, Kaleb E Smith, Wei-Hsuan Lo-Ciganic, Jiang Bian, Yonghui Wu
The progress in natural language processing (NLP) using large language models (LLMs) has greatly improved patient information extraction from clinical narratives.
no code implementations • 11 Dec 2023 • Cheng Peng, Xi Yang, Aokun Chen, Zehao Yu, Kaleb E Smith, Anthony B Costa, Mona G Flores, Jiang Bian, Yonghui Wu
Objective To solve major clinical natural language processing (NLP) tasks using a unified text-to-text learning architecture based on a generative large language model (LLM) via prompt tuning.
1 code implementation • CVPR 2024 • Zehao Yu, Anpei Chen, Binbin Huang, Torsten Sattler, Andreas Geiger
Recently, 3D Gaussian Splatting has demonstrated impressive novel view synthesis results, reaching high fidelity and efficiency.
no code implementations • 10 Oct 2023 • Cheng Peng, Xi Yang, Kaleb E Smith, Zehao Yu, Aokun Chen, Jiang Bian, Yonghui Wu
We evaluated the transfer learning ability of the prompt-based learning algorithms in a cross-institution setting.
no code implementations • 29 Aug 2023 • Yuting Xiao, Jingwei Xu, Zehao Yu, Shenghua Gao
This paper presents \textbf{DebSDF} to address these challenges, focusing on the utilization of uncertainty in monocular priors and the bias in SDF-based volume rendering.
no code implementations • 31 Mar 2023 • Aman Pathak, Zehao Yu, Daniel Paredes, Elio Paul Monsour, Andrea Ortiz Rocha, Juan P. Brito, Naykky Singh Ospina, Yonghui Wu
The ultrasound characteristics of thyroid nodules guide the evaluation of thyroid cancer in patients with thyroid nodules.
no code implementations • 31 Mar 2023 • Aokun Chen, Daniel Paredes, Zehao Yu, Xiwei Lou, Roberta Brunson, Jamie N. Thomas, Kimberly A. Martinez, Robert J. Lucero, Tanja Magoc, Laurence M. Solberg, Urszula A. Snigurska, Sarah E. Ser, Mattia Prosperi, Jiang Bian, Ragnhildur I. Bjarnadottir, Yonghui Wu
To assist in the diagnosis and phenotyping of delirium, we formed an expert panel to categorize diverse delirium symptoms, composed annotation guidelines, created a delirium corpus with diverse delirium symptoms, and developed NLP methods to extract delirium symptoms from clinical notes.
no code implementations • 14 Mar 2023 • Aokun Chen, Zehao Yu, Xi Yang, Yi Guo, Jiang Bian, Yonghui Wu
Materials and methods: We developed NLP systems for medication mention extraction, event classification (indicating medication changes discussed or not), and context classification to classify medication changes context into 5 orthogonal dimensions related to drug changes.
no code implementations • 14 Mar 2023 • Cheng Peng, Xi Yang, Zehao Yu, Jiang Bian, William R. Hogan, Yonghui Wu
GatorTron-MRC achieves the best strict and lenient F1-scores for concept extraction, outperforming previous deep learning models on the two datasets by 1%~3% and 0. 7%~1. 3%, respectively.
Clinical Concept Extraction Machine Reading Comprehension +3
no code implementations • 6 Dec 2022 • Zehao Yu, Xi Yang, Chong Dang, Prakash Adekkanattu, Braja Gopal Patra, Yifan Peng, Jyotishman Pathak, Debbie L. Wilson, Ching-Yuan Chang, Wei-Hsuan Lo-Ciganic, Thomas J. George, William R. Hogan, Yi Guo, Jiang Bian, Yonghui Wu
Objective: We aim to develop an open-source natural language processing (NLP) package, SODA (i. e., SOcial DeterminAnts), with pre-trained transformer models to extract social determinants of health (SDoH) for cancer patients, examine the generalizability of SODA to a new disease domain (i. e., opioid use), and evaluate the extraction rate of SDoH using cancer populations.
1 code implementation • CVPR 2023 • Ruoyu Wang, Zehao Yu, Shenghua Gao
PlaneDepth estimates the depth distribution using a Laplacian Mixture Model based on orthogonal planes for an input image.
1 code implementation • 1 Jun 2022 • Zehao Yu, Songyou Peng, Michael Niemeyer, Torsten Sattler, Andreas Geiger
Motivated by recent advances in the area of monocular geometry prediction, we systematically explore the utility these cues provide for improving neural implicit surface reconstruction.
3 code implementations • 31 May 2022 • Kashyap Chitta, Aditya Prakash, Bernhard Jaeger, Zehao Yu, Katrin Renz, Andreas Geiger
At the time of submission, TransFuser outperforms all prior work on the CARLA leaderboard in terms of driving score by a large margin.
Ranked #6 on Autonomous Driving on CARLA Leaderboard
no code implementations • 10 Aug 2021 • Zehao Yu, Xi Yang, Chong Dang, Songzi Wu, Prakash Adekkanattu, Jyotishman Pathak, Thomas J. George, William R. Hogan, Yi Guo, Jiang Bian, Yonghui Wu
In this study, we examined two state-of-the-art transformer-based NLP models, including BERT and RoBERTa, to extract SBDoH concepts from clinical narratives, applied the best performing model to extract SBDoH concepts on a lung cancer screening patient cohort, and examined the difference of SBDoH information between NLP extracted results and structured EHRs (SBDoH information captured in standard vocabularies such as the International Classification of Diseases codes).
1 code implementation • 19 Jul 2021 • Xi Yang, Zehao Yu, Yi Guo, Jiang Bian, Yonghui Wu
The goal of this study is to systematically explore three widely used transformer-based models (i. e., BERT, RoBERTa, and XLNet) for clinical relation extraction and develop an open-source package with clinical pre-trained transformer-based models to facilitate information extraction in the clinical domain.
2 code implementations • ICLR 2022 • Dongze Lian, Zehao Yu, Xing Sun, Shenghua Gao
Our proposed AS-MLP obtains 51. 5 mAP on the COCO validation set and 49. 5 MS mIoU on the ADE20K dataset, which is competitive compared to the transformer-based architectures.
Ranked #13 on Semantic Segmentation on DensePASS
1 code implementation • 15 Jul 2020 • Zehao Yu, Lei Jin, Shenghua Gao
Furthermore, because those textureless regions in indoor scenes (e. g., wall, floor, roof, \etc) usually correspond to planar regions, we propose to leverage superpixels as a plane prior.
1 code implementation • CVPR 2020 • Zehao Yu, Shenghua Gao
On one hand, the high-resolution depth map, the data-adaptive propagation method and the Gauss-Newton layer jointly guarantee the effectiveness of our method.
1 code implementation • 4 Jul 2019 • Dongze Lian, Zehao Yu, Shenghua Gao
There are two merits for our two-stage solution based gaze following: i) our solution mimics the behavior of human in gaze following, therefore it is more psychological plausible; ii) besides using heatmap to supervise the output of our network, we can also leverage gaze direction to facilitate the training of gaze direction pathway, therefore our network can be more robustly trained.
1 code implementation • CVPR 2019 • Zehao Yu, Jia Zheng, Dongze Lian, Zihan Zhou, Shenghua Gao
In the first stage, we train a CNN to map each pixel to an embedding space where pixels from the same plane instance have similar embeddings.
Ranked #1 on Plane Instance Segmentation on NYU Depth v2
no code implementations • ECCV 2018 • Guosheng Hu, Li Liu, Yang Yuan, Zehao Yu, Yang Hua, Zhihong Zhang, Fumin Shen, Ling Shao, Timothy Hospedales, Neil Robertson, Yongxin Yang
To advance subtle expression recognition, we contribute a Large-scale Subtle Emotions and Mental States in the Wild database (LSEMSW).
1 code implementation • 12 Sep 2017 • Guosheng Hu, Yuxin Hu, Kai Yang, Zehao Yu, Flood Sung, Zhihong Zhang, Fei Xie, Jianguo Liu, Neil Robertson, Timothy Hospedales, Qiangwei Miemie
We propose a novel investment decision strategy (IDS) based on deep learning.
Computational Finance