Search Results for author: Yuhang Zhang

Found 28 papers, 10 papers with code

Faceptor: A Generalist Model for Face Perception

3 code implementations14 Mar 2024 Lixiong Qin, Mei Wang, Xuannan Liu, Yuhang Zhang, Wei Deng, Xiaoshuai Song, Weiran Xu, Weihong Deng

This design enhances the unification of model structure while improving application efficiency in terms of storage overhead.

Age Estimation Attribute +3

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

UMG-CLIP: A Unified Multi-Granularity Vision Generalist for Open-World Understanding

no code implementations12 Jan 2024 Bowen Shi, Peisen Zhao, Zichen Wang, Yuhang Zhang, Yaoming Wang, Jin Li, Wenrui Dai, Junni Zou, Hongkai Xiong, Qi Tian, Xiaopeng Zhang

Vision-language foundation models, represented by Contrastive language-image pre-training (CLIP), have gained increasing attention for jointly understanding both vision and textual tasks.

Panoptic Segmentation Retrieval +1

DeLR: Active Learning for Detection with Decoupled Localization and Recognition Query

no code implementations28 Dec 2023 Yuhang Zhang, Yuang Deng, Xiaopeng Zhang, Jie Li, Robert C. Qiu, Qi Tian

In DeLR, the query is based on region-level, and we only annotate the object region that is queried; 2) Instead of directly providing both localization and recognition annotations, we separately query the two components, and thus reduce the recognition budget with the pseudo class labels provided by the model.

Active Learning Object +2

AdvCloak: Customized Adversarial Cloak for Privacy Protection

no code implementations22 Dec 2023 Xuannan Liu, Yaoyao Zhong, Xing Cui, Yuhang Zhang, Peipei Li, Weihong Deng

This strategy initially focuses on adapting the masks to the unique individual faces via image-specific training and then enhances their feature-level generalization ability to diverse facial variations of individuals via person-specific training.

Vision-based Learning for Drones: A Survey

no code implementations8 Dec 2023 Jiaping Xiao, Rangya Zhang, Yuhang Zhang, Mir Feroskhan

Drones as advanced cyber-physical systems are undergoing a transformative shift with the advent of vision-based learning, a field that is rapidly gaining prominence due to its profound impact on drone autonomy and functionality.

Decision Making

MARVEL: Multi-Agent Reinforcement-Learning for Large-Scale Variable Speed Limits

no code implementations18 Oct 2023 Yuhang Zhang, Marcos Quinones-Grueiro, Zhiyao Zhang, Yanbing Wang, William Barbour, Gautam Biswas, Daniel Work

Variable Speed Limit (VSL) control acts as a promising highway traffic management strategy with worldwide deployment, which can enhance traffic safety by dynamically adjusting speed limits according to real-time traffic conditions.

Decision Making Management +2

Investigating the Robustness and Properties of Detection Transformers (DETR) Toward Difficult Images

no code implementations12 Oct 2023 Zhao Ning Zou, Yuhang Zhang, Robert Wijaya

We studied this issue by measuring the performance of DETR with different experiments and benchmarking the network with convolutional neural network (CNN) based detectors like YOLO and Faster-RCNN.

Benchmarking object-detection +1

Constructing Synthetic Treatment Groups without the Mean Exchangeability Assumption

no code implementations28 Sep 2023 Yuhang Zhang, Yue Liu, Zhihua Zhang

Motivated by the synthetic control method, we construct a synthetic treatment group for the target population by a weighted mixture of treatment groups of source populations.

Calibration-based Dual Prototypical Contrastive Learning Approach for Domain Generalization Semantic Segmentation

1 code implementation25 Sep 2023 Muxin Liao, Shishun Tian, Yuhang Zhang, Guoguang Hua, Wenbin Zou, Xia Li

Based on these observations, a calibration-based dual prototypical contrastive learning (CDPCL) approach is proposed to reduce the domain discrepancy between the learned class-wise features and the prototypes of different domains for domain generalization semantic segmentation.

Contrastive Learning Domain Generalization +1

Enhancing Generalization of Universal Adversarial Perturbation through Gradient Aggregation

1 code implementation ICCV 2023 Xuannan Liu, Yaoyao Zhong, Yuhang Zhang, Lixiong Qin, Weihong Deng

Deep neural networks are vulnerable to universal adversarial perturbation (UAP), an instance-agnostic perturbation capable of fooling the target model for most samples.


CAV Traffic Control to Mitigate the Impact of Congestion from Bottlenecks: A Linear Quadratic Regulator Approach and Microsimulation Study

no code implementations17 Jun 2023 Suyash C. Vishnoi, Junyi Ji, MirSaleh Bahavarnia, Yuhang Zhang, Ahmad F. Taha, Christian G. Claudel, Daniel B. Work

The effectiveness of the proposed traffic control algorithms is tested using a traffic control example and compared with existing proportional-integral (PI)- and model predictive control (MPC)- based controllers from the literature.

Model Predictive Control

Detecting Socially Abnormal Highway Driving Behaviors via Recurrent Graph Attention Networks

1 code implementation23 Apr 2023 Yue Hu, Yuhang Zhang, Yanbing Wang, Daniel Work

In this work, we consider the problem of detecting a variety of socially abnormal driving behaviors, i. e., behaviors that do not conform to the behavior of other nearby drivers.

Anomaly Detection Graph Attention

Model and Data Agreement for Learning with Noisy Labels

1 code implementation2 Dec 2022 Yuhang Zhang, Weihong Deng, Xingchen Cui, Yunfeng Yin, Hongzhi Shi, Dongchao Wen

We introduce mean point ensemble to utilize a more robust loss function and more information from unselected samples to reduce error accumulation from the model perspective.

Learning with noisy labels

Learn From All: Erasing Attention Consistency for Noisy Label Facial Expression Recognition

1 code implementation21 Jul 2022 Yuhang Zhang, Chengrui Wang, Xu Ling, Weihong Deng

We find that FER models remember noisy samples by focusing on a part of the features that can be considered related to the noisy labels instead of learning from the whole features that lead to the latent truth.

Facial Expression Recognition Facial Expression Recognition (FER) +1

Observer-Based Coordinated Tracking Control for Nonlinear Multi-Agent Systems with Intermittent Communication under Heterogeneous Coupling Framework

no code implementations29 Jun 2022 Yuhang Zhang, Yulian Jiang, Shenquan Wang

In this article, the observer-based coordinated tracking control problem for a class of nonlinear multi-agent systems(MASs) with intermittent communication and information constraints is studied under dynamic switching topology.


Learning Efficient Representations for Enhanced Object Detection on Large-scene SAR Images

no code implementations22 Jan 2022 Siyan Li, Yue Xiao, Yuhang Zhang, Lei Chu, Robert C. Qiu

It is a challenging problem to detect and recognize targets on complex large-scene Synthetic Aperture Radar (SAR) images.

object-detection Object Detection

One-Bit Active Query With Contrastive Pairs

no code implementations CVPR 2022 Yuhang Zhang, Xiaopeng Zhang, Lingxi Xie, Jie Li, Robert C. Qiu, Hengtong Hu, Qi Tian

The Yes query is treated as positive pairs of the queried category for contrastive pulling, while the No query is treated as hard negative pairs for contrastive repelling.

Active Learning Contrastive Learning

Relative Uncertainty Learning for Facial Expression Recognition

1 code implementation NeurIPS 2021 Yuhang Zhang, Chengrui Wang, Weihong Deng

To quantify these uncertainties and achieve good performance under noisy data, we regard uncertainty as a relative concept and propose an innovative uncertainty learning method called Relative Uncertainty Learning (RUL).

Facial Expression Recognition Facial Expression Recognition (FER)

Steadily Learn to Drive with Virtual Memory

no code implementations16 Feb 2021 Yuhang Zhang, Yao Mu, Yujie Yang, Yang Guan, Shengbo Eben Li, Qi Sun, Jianyu Chen

Reinforcement learning has shown great potential in developing high-level autonomous driving.

Autonomous Driving

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