most citedSalience DETR: Enhancing Detection Transformer with Hierarchical Salience Filtering Refinement

3 citations · 3 across the 3 of their papers we have counts for

collaborators

5 papers

cs.LG2024

Discovering Common Information in Multi-view Data

Qi Zhang, Mingfei Lu, Shujian Yu +2

We introduce an innovative and mathematically rigorous definition for computing common information from multi-view data, drawing inspiration from Gács-Körner common information in…

cs.CV20243 cited

Salience DETR: Enhancing Detection Transformer with Hierarchical Salience Filtering Refinement

Xiuquan Hou, Meiqin Liu, Senlin Zhang +2

DETR-like methods have significantly increased detection performance in an end-to-end manner. The mainstream two-stage frameworks of them perform dense self-attention and select a…

cs.RO2024

Hierarchical Large Language Models in Cloud Edge End Architecture for Heterogeneous Robot Cluster Control

Zhirong Luan, Yujun Lai, Rundong Huang +4

Despite their powerful semantic understanding and code generation capabilities, Large Language Models (LLMs) still face challenges when dealing with complex tasks. Multi agent stra…

cs.CV2023

IA-LSTM: Interaction-Aware LSTM for Pedestrian Trajectory Prediction

Yuehai Chen

Predicting the trajectory of pedestrians in crowd scenarios is indispensable in self-driving or autonomous mobile robot field because estimating the future locations of pedestrians…

cs.CV2023

Learning Discriminative Features for Crowd Counting

Yuehai Chen, Qingzhong Wang, Jing Yang +3

Crowd counting models in highly congested areas confront two main challenges: weak localization ability and difficulty in differentiating between foreground and background, leading…