Search Results for author: Jianing Qiu

Found 19 papers, 8 papers with code

Dietary Assessment with Multimodal ChatGPT: A Systematic Analysis

no code implementations14 Dec 2023 Frank P. -W. Lo, Jianing Qiu, Zeyu Wang, Junhong Chen, Bo Xiao, Wu Yuan, Stamatia Giannarou, Gary Frost, Benny Lo

Although artificial intelligence (AI)-based solutions have been devised to automate the dietary assessment process, these prior AI methodologies encounter challenges in their ability to generalize across a diverse range of food types, dietary behaviors, and cultural contexts.

Image Captioning Scene Understanding

Aria-NeRF: Multimodal Egocentric View Synthesis

no code implementations11 Nov 2023 Jiankai Sun, Jianing Qiu, Chuanyang Zheng, John Tucker, Javier Yu, Mac Schwager

The construction of a NeRF-like model from an egocentric image sequence plays a pivotal role in understanding human behavior and holds diverse applications within the realms of VR/AR.

CauDR: A Causality-inspired Domain Generalization Framework for Fundus-based Diabetic Retinopathy Grading

no code implementations27 Sep 2023 Hao Wei, Peilun Shi, Juzheng Miao, Minqing Zhang, Guitao Bai, Jianing Qiu, Furui Liu, Wu Yuan

Building on this, a causality-inspired diabetic retinopathy grading framework named CauDR was developed to eliminate spurious correlations and achieve more generalizable DR diagnostics.

Diabetic Retinopathy Grading Domain Generalization

AROID: Improving Adversarial Robustness through Online Instance-wise Data Augmentation

no code implementations12 Jun 2023 Lin Li, Jianing Qiu, Michael Spratling

This allows our method to efficiently explore a large search space for a more effective DA policy and evolve the policy as training progresses.

Adversarial Robustness Data Augmentation

Generalist Vision Foundation Models for Medical Imaging: A Case Study of Segment Anything Model on Zero-Shot Medical Segmentation

1 code implementation25 Apr 2023 Peilun Shi, Jianing Qiu, Sai Mu Dalike Abaxi, Hao Wei, Frank P. -W. Lo, Wu Yuan

In this paper, we examine the recent Segment Anything Model (SAM) on medical images, and report both quantitative and qualitative zero-shot segmentation results on nine medical image segmentation benchmarks, covering various imaging modalities, such as optical coherence tomography (OCT), magnetic resonance imaging (MRI), and computed tomography (CT), as well as different applications including dermatology, ophthalmology, and radiology.

Computed Tomography (CT) Image Segmentation +4

Large AI Models in Health Informatics: Applications, Challenges, and the Future

1 code implementation21 Mar 2023 Jianing Qiu, Lin Li, Jiankai Sun, Jiachuan Peng, Peilun Shi, Ruiyang Zhang, Yinzhao Dong, Kyle Lam, Frank P. -W. Lo, Bo Xiao, Wu Yuan, Ningli Wang, Dong Xu, Benny Lo

Large AI models, or foundation models, are models recently emerging with massive scales both parameter-wise and data-wise, the magnitudes of which can reach beyond billions.

Decision Making Drug Discovery +1

EVEN: An Event-Based Framework for Monocular Depth Estimation at Adverse Night Conditions

no code implementations8 Feb 2023 Peilun Shi, Jiachuan Peng, Jianing Qiu, Xinwei Ju, Frank Po Wen Lo, Benny Lo

Comprehensive experiments have been conducted, and the impact of different adverse weather combinations on the performance of framework has also been investigated.

Autonomous Driving Monocular Depth Estimation

MenuAI: Restaurant Food Recommendation System via a Transformer-based Deep Learning Model

no code implementations15 Oct 2022 Xinwei Ju, Frank Po Wen Lo, Jianing Qiu, Peilun Shi, Jiachuan Peng, Benny Lo

The promising results, with accuracy ranging from 77. 2% to 99. 5%, have demonstrated the great potential of LTR model in addressing food recommendation problems.

Food recommendation Learning-To-Rank +2

Mining Discriminative Food Regions for Accurate Food Recognition

1 code implementation8 Jul 2022 Jianing Qiu, Frank P. -W. Lo, Yingnan Sun, Siyao Wang, Benny Lo

Taking inspiration from Adversarial Erasing, a strategy that progressively discovers discriminative object regions for weakly supervised semantic segmentation, we propose a novel network architecture in which a primary network maintains the base accuracy of classifying an input image, an auxiliary network adversarially mines discriminative food regions, and a region network classifies the resulting mined regions.

Food Recognition Weakly supervised Semantic Segmentation +1

Egocentric Human Trajectory Forecasting with a Wearable Camera and Multi-Modal Fusion

1 code implementation1 Nov 2021 Jianing Qiu, Lipeng Chen, Xiao Gu, Frank P. -W. Lo, Ya-Yen Tsai, Jiankai Sun, Jiaqi Liu, Benny Lo

To this end, a novel egocentric human trajectory forecasting dataset was constructed, containing real trajectories of people navigating in crowded spaces wearing a camera, as well as extracted rich contextual data.

Trajectory Forecasting

TransAction: ICL-SJTU Submission to EPIC-Kitchens Action Anticipation Challenge 2021

1 code implementation28 Jul 2021 Xiao Gu, Jianing Qiu, Yao Guo, Benny Lo, Guang-Zhong Yang

In this report, the technical details of our submission to the EPIC-Kitchens Action Anticipation Challenge 2021 are given.

Action Anticipation

Egocentric Image Captioning for Privacy-Preserved Passive Dietary Intake Monitoring

no code implementations1 Jul 2021 Jianing Qiu, Frank P. -W. Lo, Xiao Gu, Modou L. Jobarteh, Wenyan Jia, Tom Baranowski, Matilda Steiner-Asiedu, Alex K. Anderson, Megan A McCrory, Edward Sazonov, Mingui Sun, Gary Frost, Benny Lo

In this paper, we propose a privacy-preserved secure solution (i. e., egocentric image captioning) for dietary assessment with passive monitoring, which unifies food recognition, volume estimation, and scene understanding.

Food Recognition Image Captioning +1

Indoor Future Person Localization from an Egocentric Wearable Camera

no code implementations6 Mar 2021 Jianing Qiu, Frank P. -W. Lo, Xiao Gu, Yingnan Sun, Shuo Jiang, Benny Lo

Accurate prediction of future person location and movement trajectory from an egocentric wearable camera can benefit a wide range of applications, such as assisting visually impaired people in navigation, and the development of mobility assistance for people with disability.

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