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cs.CV2026

Faster or Stronger: Towards Flexible Visual Place Recognition via Weighted Aggregation and Token Pruning

Zichao Zeng, June Moh Goo, Junwei Zheng +4

Visual Place Recognition (VPR) aims to match a query image to reference images of the same place in a large-scale database. Recent state-of-the-art methods employ Vision Transforme…

cs.CV2026

Exploring Single Domain Generalization of LiDAR-based Semantic Segmentation under Imperfect Labels

Weitong Kong, Zichao Zeng, Di Wen +5

Accurate perception is critical for vehicle safety, with LiDAR as a key enabler in autonomous driving. To ensure robust performance across environments, sensor types, and weather c…

cs.CV2026

A Comprehensive Survey on Deep Learning-Based LiDAR Super-Resolution for Autonomous Driving

June Moh Goo, Zichao Zeng, Jan Boehm

LiDAR sensors are often considered essential for autonomous driving, but high-resolution sensors remain expensive while affordable low-resolution sensors produce sparse point cloud…

cs.CV2025

Real-Time LiDAR Super-Resolution via Frequency-Aware Multi-Scale Fusion

June Moh Goo, Zichao Zeng, Jan Boehm

LiDAR super-resolution addresses the challenge of achieving high-quality 3D perception from cost-effective, low-resolution sensors. While recent transformer-based approaches like T…

cs.CV2024

Hybrid-Segmentor: A Hybrid Approach to Automated Fine-Grained Crack Segmentation in Civil Infrastructure

June Moh Goo, Xenios Milidonis, Alessandro Artusi +2

Detecting and segmenting cracks in infrastructure, such as roads and buildings, is crucial for safety and cost-effective maintenance. In spite of the potential of deep learning, th…

cs.CV2024

Zero-shot detection of buildings in mobile LiDAR using Language Vision Model

June Moh Goo, Zichao Zeng, Jan Boehm

Recent advances have demonstrated that Language Vision Models (LVMs) surpass the existing State-of-the-Art (SOTA) in two-dimensional (2D) computer vision tasks, motivating attempts…