activity
20162025
most citedMultispectral Deep Neural Networks for Pedestrian Detection

53 citations · 63 across the 10 of their papers we have counts for

collaborators

10 papers

cs.LG2025

Contrastive Private Data Synthesis via Weighted Multi-PLM Fusion

Tianyuan Zou, Yang Liu, Peng Li +6

Substantial quantity and high quality are the golden rules of making a good training dataset with sample privacy protection equally important. Generating synthetic samples that res…

cs.CV2025

IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain

Zhe Wang, Xiaoliang Huo, Siqi Fan +3

In autonomous driving, The perception capabilities of the ego-vehicle can be improved with roadside sensors, which can provide a holistic view of the environment. However, existing…

cs.CV2024

EMIFF: Enhanced Multi-scale Image Feature Fusion for Vehicle-Infrastructure Cooperative 3D Object Detection

Zhe Wang, Siqi Fan, Xiaoliang Huo +5

In autonomous driving, cooperative perception makes use of multi-view cameras from both vehicles and infrastructure, providing a global vantage point with rich semantic context of…

eess.IV2023

Conditional Perceptual Quality Preserving Image Compression

Tongda Xu, Qian Zhang, Yanghao Li +7

We propose conditional perceptual quality, an extension of the perceptual quality defined in \citet{blau2018perception}, by conditioning it on user defined information. Specificall…

cs.LG20231 cited

K-means Clustering Based Feature Consistency Alignment for Label-free Model Evaluation

Shuyu Miao, Lin Zheng, Jingjing Liu +1

The label-free model evaluation aims to predict the model performance on various test sets without relying on ground truths. The main challenge of this task is the absence of label…

cs.CV2023

Calibration-free BEV Representation for Infrastructure Perception

Siqi Fan, Zhe Wang, Xiaoliang Huo +2

Effective BEV object detection on infrastructure can greatly improve traffic scenes understanding and vehicle-toinfrastructure (V2I) cooperative perception. However, cameras instal…