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Wenpeng Li

4 accepted papers

2024

Refinement Bird's Eye View Feature for 3D Lane Detection with Dual-Branch View Transformation Module

ICASSP 2024accepted

Detecting 3D lane lines from images is a fundamental challenge and an ill-posed problem in autonomous driving. Existing methods are limited by scene robustness and computational efficiency. This paper introduces an innovative 3D lane detection method that addresses the challenges of lane detection i…

Cited by 0SourceScholar
2023

Adaptive Patchwork: Real-Time Ground Segmentation for 3D Point Cloud With Adaptive Partitioning and Spatial-Temporal Context

RA-L 2023

Ground segmentation is a fundamental task in the field of 3D perception using 3D LiDAR sensors. Several ground segmentation methods have been proposed, but they often suffer from mis-segmentation, especially missed detection, due to poor noise removal, unreasonable ground pre-blocking and lack of re

Cited by 8SourceScholar
2023

TrimTail: Low-Latency Streaming ASR with Simple But Effective Spectrogram-Level Length Penalty

ICASSP 2023accepted

In this paper, we present TrimTail, a simple but effective emission regularization method to improve the latency of streaming ASR models. The core idea of TrimTail is to apply length penalty (i.e., by trimming trailing frames, see Fig. 1-(b)) directly on the spectrogram of input utterances, which do…

Cited by 0SourceScholar
2022

Personalized Federated Learning via Variational Bayesian Inference

ICML 2022spotlight

Federated learning faces huge challenges from model overfitting due to the lack of data and statistical diversity among clients. To address these challenges, this paper proposes a novel personalized federated learning method via Bayesian variational inference named pFedBayes. To alleviate the overfi…

Cited by 122SourcePDFScholar