4 papers
PointAD+: Learning Hierarchical Representations for Zero-shot 3D Anomaly Detection
Qihang Zhou, Shibo He, Jiangtao Yan +2
In this paper, we aim to transfer CLIP's robust 2D generalization capabilities to identify 3D anomalies across unseen objects of highly diverse class semantics. To this end, we pro…
FairDD: Fair Dataset Distillation
Qihang Zhou, Shenhao Fang, Shibo He +2
Condensing large datasets into smaller synthetic counterparts has demonstrated its promise for image classification. However, previous research has overlooked a crucial concern in…
LearnAct: Few-Shot Mobile GUI Agent with a Unified Demonstration Benchmark
Guangyi Liu, Pengxiang Zhao, Liang Liu +6
Mobile GUI agents show promise in automating tasks but face generalization challenges in diverse real-world scenarios. Traditional approaches using pre-training or fine-tuning with…
PointAD: Comprehending 3D Anomalies from Points and Pixels for Zero-shot 3D Anomaly Detection
Qihang Zhou, Jiangtao Yan, Shibo He +2
Zero-shot (ZS) 3D anomaly detection is a crucial yet unexplored field that addresses scenarios where target 3D training samples are unavailable due to practical concerns like priva…