Publications (16)
Preferred Synthesis of Armchair Transition Metal Dichalcogenide Nanotubes
Abid, Luneng Zhao, Ju Huang +25
In this work, we present the synthesis of transition-metal dichalcogenide (TMDC) nanotubes with a preferred chiral angle. SnS2, MoS2, and WS2 are formed with high yield and structu…
ViCo3D: Empowering LiDAR-based Collaborative 3D Object Detection with Vision Foundation Models
Haojie Ren, Songrui Luo, Lingfeng Wang +6
The paper introduces ViCo3D, a framework that leverages vision foundation models to enrich LiDAR bird's-eye-view features for collaborative 3D object detection in V2X scenarios, ac…
EmbodiedBrain: Expanding Performance Boundaries of Task Planning for Embodied Intelligence
Ding Zou, Feifan Wang, Mengyu Ge +17
The realization of Artificial General Intelligence (AGI) necessitates Embodied AI agents capable of robust spatial perception, effective task planning, and adaptive execution in ph…
Semantic Labeling in Very High Resolution Images via a Self-Cascaded Convolutional Neural Network
Yongcheng Liu, Bin Fan, Lingfeng Wang +3
Semantic labeling for very high resolution (VHR) images in urban areas, is of significant importance in a wide range of remote sensing applications. However, many confusing manmade…
A Robust Power Grid Defense Model Considering Load Demand and Wind Generation Uncertainties
Yingmeng Xiang, Xiaohu Zhang, Di Shi +3
It is a major task to develop effective strategies for defending the power system against deliberate attacks. It is critical to comprehensively consider the human-related and envir…
Hybrid CNN-Transformer Model For Facial Affect Recognition In the ABAW4 Challenge
Lingfeng Wang, Haocheng Li, Chunyin Liu
This paper describes our submission to the fourth Affective Behavior Analysis (ABAW) competition. We proposed a hybrid CNN-Transformer model for the Multi-Task-Learning (MTL) and L…
Uncertainty-Aware Offline Data-Driven Multi-Objective Optimization
Huanbo Lyu, Miqing Li, Shiqiao Zhou +7
In offline data-driven multi-objective optimization (MOO), optimization is performed using surrogate models trained only on an offline dataset. These surrogate models contain inher…
Multi-modal Multi-label Facial Action Unit Detection with Transformer
Lingfeng Wang, Shisen Wang, Jin Qi
Facial Action Coding System is an important approach of facial expression analysis.This paper describes our submission to the third Affective Behavior Analysis (ABAW) 2022 competit…
A Novel Mutual Insurance Model for Hedging Against Cyber Risks in Power Systems Deploying Smart Technologies
Pikkin Lau, Lingfeng Wang, Wei Wei +2
In this paper, a novel cyber-insurance model design is proposed based on system risk evaluation with smart technology applications. The cyber insurance policy for power systems is…
Deep Discriminative Clustering Analysis
Jianlong Chang, Yiwen Guo, Lingfeng Wang +3
Traditional clustering methods often perform clustering with low-level indiscriminative representations and ignore relationships between patterns, resulting in slight achievements…
A Multi-task Mean Teacher for Semi-supervised Facial Affective Behavior Analysis
Lingfeng Wang, Shisen Wang, Jin Qi +1
Affective Behavior Analysis is an important part in human-computer interaction. Existing multi-task affective behavior recognition methods suffer from the problem of incomplete lab…
Analytic Deep Learning-based Surrogate Model for Operational Planning with Dynamic TTC Constraints
Gao Qiu, Youbo Liu, Junyong Liu +4
The increased penetration of wind power introduces more operational changes of critical corridors and the traditional time-consuming transient stability constrained total transfer…
HiMTok: Learning Hierarchical Mask Tokens for Image Segmentation with Large Multimodal Model
Tao Wang, Changxu Cheng, Lingfeng Wang +2
The remarkable performance of large multimodal models (LMMs) has attracted significant interest from the image segmentation community. To align with the next-token-prediction parad…
Technique Report of CVPR 2024 PBDL Challenges
Ying Fu, Yu Li, Shaodi You +96
The intersection of physics-based vision and deep learning presents an exciting frontier for advancing computer vision technologies. By leveraging the principles of physics to info…
ALTo: Adaptive-Length Tokenizer for Autoregressive Mask Generation
Lingfeng Wang, Hualing Lin, Senda Chen +5
While humans effortlessly draw visual objects and shapes by adaptively allocating attention based on their complexity, existing multimodal large language models (MLLMs) remain cons…
Machine learning for predicting fatigue properties of additively manufactured materials
Min Yi, Ming Xue, Peihong Cong +6
Fatigue properties of additively manufactured (AM) materials depend on many factors such as AM processing parameter, microstructure, residual stress, surface roughness, porosities,…