activity
20232025
most citedMultimodal 3D Object Detection on Unseen Domains

1 citations · 1 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2025

Joint Training of Image Generator and Detector for Road Defect Detection

Kuan-Chuan Peng

Road defect detection is important for road authorities to reduce the vehicle damage caused by road defects. Considering the practical scenarios where the defect detectors are typi…

cs.CV2025

Improving Open-World Object Localization by Discovering Background

Ashish Singh, Michael J. Jones, Kuan-Chuan Peng +3

Our work addresses the problem of learning to localize objects in an open-world setting, i.e., given the bounding box information of a limited number of object classes during train…

cs.CV2025

PF3Det: A Prompted Foundation Feature Assisted Visual LiDAR 3D Detector

Kaidong Li, Tianxiao Zhang, Kuan-Chuan Peng +1

3D object detection is crucial for autonomous driving, leveraging both LiDAR point clouds for precise depth information and camera images for rich semantic information. Therefore,…

cs.CV2024

Towards Zero-shot 3D Anomaly Localization

Yizhou Wang, Kuan-Chuan Peng, Yun Fu

3D anomaly detection and localization is of great significance for industrial inspection. Prior 3D anomaly detection and localization methods focus on the setting that the testing…

cs.CV20241 cited

Multimodal 3D Object Detection on Unseen Domains

Deepti Hegde, Suhas Lohit, Kuan-Chuan Peng +2

LiDAR datasets for autonomous driving exhibit biases in properties such as point cloud density, range, and object dimensions. As a result, object detection networks trained and eva…

cs.CV2024

Equivariant Spatio-Temporal Self-Supervision for LiDAR Object Detection

Deepti Hegde, Suhas Lohit, Kuan-Chuan Peng +2

Popular representation learning methods encourage feature invariance under transformations applied at the input. However, in 3D perception tasks like object localization and segmen…