activity
20222024
most citedPolarMix: A General Data Augmentation Technique for LiDAR Point Clouds

38 citations · 41 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

Controllable and Gradual Facial Blemishes Retouching via Physics-Based Modelling

Chenhao Shuai, Rizhao Cai, Bandara Dissanayake +5

Face retouching aims to remove facial blemishes, such as pigmentation and acne, and still retain fine-grain texture details. Nevertheless, existing methods just remove the blemishe…

cs.CV2024

Efficient Test-Time Adaptation of Vision-Language Models

Adilbek Karmanov, Dayan Guan, Shijian Lu +2

Test-time adaptation with pre-trained vision-language models has attracted increasing attention for tackling distribution shifts during the test time. Though prior studies have ach…

cs.CV20231 cited

3D Semantic Segmentation in the Wild: Learning Generalized Models for Adverse-Condition Point Clouds

Aoran Xiao, Jiaxing Huang, Weihao Xuan +6

Robust point cloud parsing under all-weather conditions is crucial to level-5 autonomy in autonomous driving. However, how to learn a universal 3D semantic segmentation (3DSS) mode…

cs.CV202238 cited

PolarMix: A General Data Augmentation Technique for LiDAR Point Clouds

Aoran Xiao, Jiaxing Huang, Dayan Guan +3

LiDAR point clouds, which are usually scanned by rotating LiDAR sensors continuously, capture precise geometry of the surrounding environment and are crucial to many autonomous det…

cs.CV20222 cited

Domain Adaptive Video Segmentation via Temporal Pseudo Supervision

Yun Xing, Dayan Guan, Jiaxing Huang +1

Video semantic segmentation has achieved great progress under the supervision of large amounts of labelled training data. However, domain adaptive video segmentation, which can mit…