1.9k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of Chinese Academy of SciencesCN72 papers
- Chinese Academy of SciencesCN70 papers
- Institute of AutomationCN57 papers
- Beijing Academy of Artificial IntelligenceCN20 papers
- Institute of Computing TechnologyCN11 papers
- Shandong Institute of AutomationCN11 papers
- University of Science and Technology of ChinaCN5 papers
- Peng Cheng LaboratoryCN4 papers
- Tsinghua UniversityCN4 papers
- Horizon Robotics (China)3 papers
- Ningbo Institute of Industrial TechnologyCN3 papers
- Tongji UniversityCN3 papers
106 papers
A Survey of Large Language Models for Perception and Measurement of Human Psychology
Yudong Li, Xiaoyi Chen, Jiawei Cai +4
Against the backdrop of the rapid advancement of Large Language Models (LLMs), their application in the field of psychology has garnered significant academic attention. A central i…
Diffusion Model-Based Data Augmentation for Enhanced Neuron Segmentation
Liuyun Jiang, Yanchao Zhang, Jinyue Guo +3
Neuron segmentation in electron microscopy (EM) aims to reconstruct the complete neuronal connectome; however, current deep learning-based methods are limited by their reliance on…
Exploring EEG and Eye Movement Fusion for Multi-Class Target RSVP-BCI
Xujin Li, Wei Wei, Kun Zhao +4
Rapid Serial Visual Presentation (RSVP)-based Brain-Computer Interfaces (BCIs) facilitate high-throughput target image detection by identifying event-related potentials (ERPs) evok…
Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training
Man Yao, Xuerui Qiu, Tianxiang Hu +7
The ambition of brain-inspired Spiking Neural Networks (SNNs) is to become a low-power alternative to traditional Artificial Neural Networks (ANNs). This work addresses two major c…
Conditional Denoising Meets Polynomial Modeling: A Flexible Decoupled Framework for Time Series Forecasting
Jintao Zhang, Mingyue Cheng, Xiaoyu Tao +2
Time series forecasting models are becoming increasingly prevalent due to their critical role in decision-making across various domains. However, most existing approaches represent…
A Hybrid Multi-Factor Network with Dynamic Sequence Modeling for Early Warning of Intraoperative Hypotension
Mingyue Cheng, Jintao Zhang, Zhiding Liu +1
Intraoperative hypotension (IOH) prediction using past physiological signals is crucial, as IOH may lead to inadequate organ perfusion and significantly elevate the risk of severe…
Human-like object concept representations emerge naturally in multimodal large language models
Changde Du, Kaicheng Fu, Bincheng Wen +10
Understanding how humans conceptualize and categorize natural objects offers critical insights into perception and cognition. With the advent of Large Language Models (LLMs), a key…
Towards Dynamic Trend Filtering through Trend Point Detection with Reinforcement Learning
Jihyeon Seong, Sekwang Oh, Jaesik Choi
Trend filtering simplifies complex time series data by applying smoothness to filter out noise while emphasizing proximity to the original data. However, existing trend filtering m…
Contrastive Learning of Person-independent Representations for Facial Action Unit Detection
Yong Li, Shiguang Shan
Facial action unit (AU) detection, aiming to classify AU present in the facial image, has long suffered from insufficient AU annotations. In this paper, we aim to mitigate this dat…
A Temporal-Spectral Fusion Transformer with Subject-Specific Adapter for Enhancing RSVP-BCI Decoding
Xujin Li, Wei Wei, Shuang Qiu +1
The Rapid Serial Visual Presentation (RSVP)-based Brain-Computer Interface (BCI) is an efficient technology for target retrieval using electroencephalography (EEG) signals. The per…
The TopCoW Challenge -- Topology-Aware Circle of Willis Segmentation for CT and MR Angiography
Kaiyuan Yang, Fabio Musio, Yihui Ma +112
The Circle of Willis (CoW) is an important network of arteries connecting major circulations of the brain. Its vascular architecture is believed to influence the risk, severity, an…
Audio-Driven Dubbing for User Generated Contents via Style-Aware Semi-Parametric Synthesis
Linsen Song, Wayne Wu, Chaoyou Fu +2
Existing automated dubbing methods are usually designed for Professionally Generated Content (PGC) production, which requires massive training data and training time to learn a per…
End-to-end Alternating Optimization for Real-World Blind Super Resolution
Zhengxiong Luo, Yan Huang, Shang Li +2
Blind Super-Resolution (SR) usually involves two sub-problems: 1) estimating the degradation of the given low-resolution (LR) image; 2) super-resolving the LR image to its high-res…
Significant Unconventional Anomalous Hall Effect in Heavy Metal/Antiferromagnetic Insulator Heterostructures
Yuhan Liang, Liang Wu, Minyi Dai +16
The anomalous Hall effect (AHE) is a quantum coherent transport phenomenon that conventionally vanishes at elevated temperatures because of thermal dephasing. Therefore, it is puzz…
Tuning Synaptic Connections instead of Weights by Genetic Algorithm in Spiking Policy Network
Duzhen Zhang, Tielin Zhang, Shuncheng Jia +2
Learning from interaction is the primary way that biological agents acquire knowledge about their environment and themselves. Modern deep reinforcement learning (DRL) explores a co…
FireFly: A High-Throughput Hardware Accelerator for Spiking Neural Networks with Efficient DSP and Memory Optimization
Jindong Li, Guobin Shen, Dongcheng Zhao +2
Spiking neural networks (SNNs) have been widely used due to their strong biological interpretability and high energy efficiency. With the introduction of the backpropagation algori…
Distributed Deep Reinforcement Learning: A Survey and A Multi-Player Multi-Agent Learning Toolbox
Qiyue Yin, Tongtong Yu, Shengqi Shen +5
With the breakthrough of AlphaGo, deep reinforcement learning becomes a recognized technique for solving sequential decision-making problems. Despite its reputation, data inefficie…
QueryProp: Object Query Propagation for High-Performance Video Object Detection
Fei He, Naiyu Gao, Jian Jia +2
Video object detection has been an important yet challenging topic in computer vision. Traditional methods mainly focus on designing the image-level or box-level feature propagatio…
BrainCog: A Spiking Neural Network based Brain-inspired Cognitive Intelligence Engine for Brain-inspired AI and Brain Simulation
Yi Zeng, Dongcheng Zhao, Feifei Zhao +16
Spiking neural networks (SNNs) have attracted extensive attentions in Brain-inspired Artificial Intelligence and computational neuroscience. They can be used to simulate biological…
Narrowing the Gap: Improved Detector Training with Noisy Location Annotations
Shaoru Wang, Jin Gao, Bing Li +1
Deep learning methods require massive of annotated data for optimizing parameters. For example, datasets attached with accurate bounding box annotations are essential for modern ob…
Heterogeneous Face Recognition via Face Synthesis with Identity-Attribute Disentanglement
Ziming Yang, Jian Liang, Chaoyou Fu +2
Heterogeneous Face Recognition (HFR) aims to match faces across different domains (e.g., visible to near-infrared images), which has been widely applied in authentication and foren…
Non-parametric power-law surrogates
Jack Murdoch Moore, Gang Yan, Eduardo G. Altmann
Power-law distributions are essential in computational and statistical investigations of extreme events and complex systems. The usual technique to generate power-law distributed d…
Weakly Aligned Feature Fusion for Multimodal Object Detection
Lu Zhang, Zhiyong Liu, Xiangyu Zhu +4
To achieve accurate and robust object detection in the real-world scenario, various forms of images are incorporated, such as color, thermal, and depth. However, multimodal data of…
SOTVerse: A User-defined Task Space of Single Object Tracking
Shiyu Hu, Xin Zhao, Kaiqi Huang
Single object tracking (SOT) research falls into a cycle -- trackers perform well on most benchmarks but quickly fail in challenging scenarios, causing researchers to doubt the ins…