Search Results for author: Pengxiang Wu

Found 21 papers, 12 papers with code

Multimodality-guided Image Style Transfer using Cross-modal GAN Inversion

no code implementations4 Dec 2023 Hanyu Wang, Pengxiang Wu, Kevin Dela Rosa, Chen Wang, Abhinav Shrivastava

Compared to IIST, such approaches provide more flexibility with text-specified styles, which are useful in scenarios where the style is hard to define with reference images.

Style Transfer

Learning to Abstain From Uninformative Data

no code implementations25 Sep 2023 Yikai Zhang, Songzhu Zheng, Mina Dalirrooyfard, Pengxiang Wu, Anderson Schneider, Anant Raj, Yuriy Nevmyvaka, Chao Chen

Learning and decision-making in domains with naturally high noise-to-signal ratio, such as Finance or Healthcare, is often challenging, while the stakes are very high.

Decision Making Learning Theory

Learning Distilled Collaboration Graph for Multi-Agent Perception

2 code implementations NeurIPS 2021 Yiming Li, Shunli Ren, Pengxiang Wu, Siheng Chen, Chen Feng, Wenjun Zhang

Our approach is validated on V2X-Sim 1. 0, a large-scale multi-agent perception dataset that we synthesized using CARLA and SUMO co-simulation.

3D Object Detection Knowledge Distillation +1

Learning to Abstain in the Presence of Uninformative Data

no code implementations29 Sep 2021 Yikai Zhang, Songzhu Zheng, Pengxiang Wu, Yuriy Nevmyvaka, Chao Chen

Learning and decision making in domains with naturally high noise-to-signal ratios – such as Finance or Public Health – can be challenging and yet extremely important.

Decision Making Learning Theory

Error-Bounded Correction of Noisy Labels

3 code implementations ICML 2020 Songzhu Zheng, Pengxiang Wu, Aman Goswami, Mayank Goswami, Dimitris Metaxas, Chao Chen

To be robust against label noise, many successful methods rely on the noisy classifiers (i. e., models trained on the noisy training data) to determine whether a label is trustworthy.

Image Classification

Enhanced MRI Reconstruction Network using Neural Architecture Search

no code implementations19 Aug 2020 Qiaoying Huang, Dong Yang, Yikun Xian, Pengxiang Wu, Jingru Yi, Hui Qu, Dimitris Metaxas

The accurate reconstruction of under-sampled magnetic resonance imaging (MRI) data using modern deep learning technology, requires significant effort to design the necessary complex neural network architectures.

MRI Reconstruction Neural Architecture Search

PC-U Net: Learning to Jointly Reconstruct and Segment the Cardiac Walls in 3D from CT Data

no code implementations18 Aug 2020 Meng Ye, Qiaoying Huang, Dong Yang, Pengxiang Wu, Jingru Yi, Leon Axel, Dimitris Metaxas

The 3D volumetric shape of the heart's left ventricle (LV) myocardium (MYO) wall provides important information for diagnosis of cardiac disease and invasive procedure navigation.

Image Segmentation Segmentation +1

Oriented Object Detection in Aerial Images with Box Boundary-Aware Vectors

1 code implementation17 Aug 2020 Jingru Yi, Pengxiang Wu, Bo Liu, Qiaoying Huang, Hui Qu, Dimitris Metaxas

To address this issue, in this work we extend the horizontal keypoint-based object detector to the oriented object detection task.

Object object-detection +3

Weakly Supervised Deep Nuclei Segmentation Using Partial Points Annotation in Histopathology Images

no code implementations10 Jul 2020 Hui Qu, Pengxiang Wu, Qiaoying Huang, Jingru Yi, Zhennan Yan, Kang Li, Gregory M. Riedlinger, Subhajyoti De, Shaoting Zhang, Dimitris N. Metaxas

To alleviate such tedious and manual effort, in this paper we propose a novel weakly supervised segmentation framework based on partial points annotation, i. e., only a small portion of nuclei locations in each image are labeled.

Segmentation Weakly supervised segmentation

MotionNet: Joint Perception and Motion Prediction for Autonomous Driving Based on Bird's Eye View Maps

2 code implementations CVPR 2020 Pengxiang Wu, Siheng Chen, Dimitris Metaxas

The backbone of MotionNet is a novel spatio-temporal pyramid network, which extracts deep spatial and temporal features in a hierarchical fashion.

3D Object Detection Autonomous Driving +2

Vertebra-Focused Landmark Detection for Scoliosis Assessment

1 code implementation9 Jan 2020 Jingru Yi, Pengxiang Wu, Qiaoying Huang, Hui Qu, Dimitris N. Metaxas

The comparison results demonstrate the merits of our method in both Cobb angle measurement and landmark detection on low-contrast and ambiguous X-ray images.

Point Cloud Processing via Recurrent Set Encoding

no code implementations25 Nov 2019 Pengxiang Wu, Chao Chen, Jingru Yi, Dimitris Metaxas

The spatial layout of the beams is regular, and this allows the beam features to be further fed into an efficient 2D convolutional neural network (CNN) for hierarchical feature aggregation.

Object-Guided Instance Segmentation for Biological Images

no code implementations20 Nov 2019 Jingru Yi, Hui Tang, Pengxiang Wu, Bo Liu, Daniel J. Hoeppner, Dimitris N. Metaxas, Lianyi Han, Wei Fan

Along with the instance normalization, the model is able to recover the target object distribution and suppress the distribution of neighboring attached objects.

Clustering Instance Segmentation +6

Label Cleaning with Likelihood Ratio Test

no code implementations25 Sep 2019 Songzhu Zheng, Pengxiang Wu, Aman Goswami, Mayank Goswami, Dimitris Metaxas, Chao Chen

To collect large scale annotated data, it is inevitable to introduce label noise, i. e., incorrect class labels.

MRI Reconstruction via Cascaded Channel-wise Attention Network

1 code implementation18 Oct 2018 Qiaoying Huang, Dong Yang, Pengxiang Wu, Hui Qu, Jingru Yi, Dimitris Metaxas

We consider an MRI reconstruction problem with input of k-space data at a very low undersampled rate.

MRI Reconstruction

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