activity
20172026
most citedBrain Inspired Cognitive Model with Attention for Self-Driving Cars

11 citations · 11 across the 5 of their papers we have counts for

collaborators

6 papers

cs.AI2026

Breakthrough the Suboptimal Stable Point in Value-Factorization-Based Multi-Agent Reinforcement Learning

Lesong Tao, Yifei Wang, Haodong Jing +4

Value factorization, a popular paradigm in MARL, faces significant theoretical and algorithmic bottlenecks: its tendency to converge to suboptimal solutions remains poorly understo…

cs.RO2026

Optimal-Horizon Social Robot Navigation in Heterogeneous Crowds

Jiamin Shi, Haolin Zhang, Yuchen Yan +3

Navigating social robots in dense, dynamic crowds is challenging due to environmental uncertainty and complex human-robot interactions. While Model Predictive Control (MPC) offers…

cs.CV2025

StructVPR++: Distill Structural and Semantic Knowledge with Weighting Samples for Visual Place Recognition

Yanqing Shen, Sanping Zhou, Jingwen Fu +3

Visual place recognition is a challenging task for autonomous driving and robotics, which is usually considered as an image retrieval problem. A commonly used two-stage strategy in…

cs.LG2020

Traffic Agent Trajectory Prediction Using Social Convolution and Attention Mechanism

Tao Yang, Zhixiong Nan, He Zhang +2

The trajectory prediction is significant for the decision-making of autonomous driving vehicles. In this paper, we propose a model to predict the trajectories of target agents arou…

cs.CV2018

Feature Selective Small Object Detection via Knowledge-based Recurrent Attentive Neural Network

Kai Yi, Zhiqiang Jian, Shitao Chen +1

At present, the performance of deep neural network in general object detection is comparable to or even surpasses that of human beings. However, due to the limitations of deep lear…

cs.CV201711 cited

Brain Inspired Cognitive Model with Attention for Self-Driving Cars

Shitao Chen, Songyi Zhang, Jinghao Shang +2

Perception-driven approach and end-to-end system are two major vision-based frameworks for self-driving cars. However, it is difficult to introduce attention and historical informa…