Search Results for author: Yue Yao

Found 14 papers, 8 papers with code

The 8th AI City Challenge

no code implementations15 Apr 2024 Shuo Wang, David C. Anastasiu, Zheng Tang, Ming-Ching Chang, Yue Yao, Liang Zheng, Mohammed Shaiqur Rahman, Meenakshi S. Arya, Anuj Sharma, Pranamesh Chakraborty, Sanjita Prajapati, Quan Kong, Norimasa Kobori, Munkhjargal Gochoo, Munkh-Erdene Otgonbold, Fady Alnajjar, Ganzorig Batnasan, Ping-Yang Chen, Jun-Wei Hsieh, Xunlei Wu, Sameer Satish Pusegaonkar, Yizhou Wang, Sujit Biswas, Rama Chellappa

The eighth AI City Challenge highlighted the convergence of computer vision and artificial intelligence in areas like retail, warehouse settings, and Intelligent Traffic Systems (ITS), presenting significant research opportunities.

Dense Video Captioning

Open-Set Facial Expression Recognition

no code implementations23 Jan 2024 Yuhang Zhang, Yue Yao, Xuannan Liu, Lixiong Qin, Wenjing Wang, Weihong Deng

Facial expression recognition (FER) models are typically trained on datasets with a fixed number of seven basic classes.

Facial Expression Recognition Facial Expression Recognition (FER) +1

Alice Benchmarks: Connecting Real World Re-Identification with the Synthetic

no code implementations6 Oct 2023 Xiaoxiao Sun, Yue Yao, Shengjin Wang, Hongdong Li, Liang Zheng

In this paper, we detail the settings of Alice benchmarks, provide an analysis of existing commonly-used domain adaptation methods, and discuss some interesting future directions.

Domain Adaptation

Training with Product Digital Twins for AutoRetail Checkout

1 code implementation18 Aug 2023 Yue Yao, Xinyu Tian, Zheng Tang, Sujit Biswas, Huan Lei, Tom Gedeon, Liang Zheng

Because the digital twins individually mimic user bias, the resulting DT training set better reflects the characteristics of the target scenario and allows us to train more effective product detection and tracking models.

The 7th AI City Challenge

no code implementations15 Apr 2023 Milind Naphade, Shuo Wang, David C. Anastasiu, Zheng Tang, Ming-Ching Chang, Yue Yao, Liang Zheng, Mohammed Shaiqur Rahman, Meenakshi S. Arya, Anuj Sharma, Qi Feng, Vitaly Ablavsky, Stan Sclaroff, Pranamesh Chakraborty, Sanjita Prajapati, Alice Li, Shangru Li, Krishna Kunadharaju, Shenxin Jiang, Rama Chellappa

The AI City Challenge's seventh edition emphasizes two domains at the intersection of computer vision and artificial intelligence - retail business and Intelligent Traffic Systems (ITS) - that have considerable untapped potential.


Large-scale Training Data Search for Object Re-identification

1 code implementation CVPR 2023 Yue Yao, Huan Lei, Tom Gedeon, Liang Zheng

We consider a scenario where we have access to the target domain, but cannot afford on-the-fly training data annotation, and instead would like to construct an alternative training set from a large-scale data pool such that a competitive model can be obtained.

Object Specificity

An Empirical Bayes Analysis of Object Trajectory Representation Models

no code implementations3 Nov 2022 Yue Yao, Daniel Goehring, Joerg Reichardt

This suggests the feasibility of using linear trajectory models in future motion prediction systems with inherent mathematical advantages.

Autonomous Driving motion prediction +1

Attribute Descent: Simulating Object-Centric Datasets on the Content Level and Beyond

2 code implementations28 Feb 2022 Yue Yao, Liang Zheng, Xiaodong Yang, Milind Napthade, Tom Gedeon

This article aims to use graphic engines to simulate a large number of training data that have free annotations and possibly strongly resemble to real-world data.

Attribute Data Augmentation +2

Disguising Personal Identity Information in EEG Signals

1 code implementation18 Oct 2020 Shiya Liu, Yue Yao, Chaoyue Xing, Tom Gedeon

The personal identity information in original EEGs are transformed into disguised ones with a CycleGANbased EEG disguising model.


Pairwise-GAN: Pose-based View Synthesis through Pair-Wise Training

1 code implementation13 Sep 2020 Xuyang Shen, Jo Plested, Yue Yao, Tom Gedeon

This inspired our research which explores the performance of two models from pixel transformation in frontal facial synthesis, Pix2Pix and CycleGAN.

Face Reconstruction Generative Adversarial Network +1

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