5 papers · 1 filter
Attention-Guided Perturbation Network for Industrial Anomaly Detection
Tingfeng Huang, Weijia Kong, Yuxuan Cheng +8
In unsupervised image anomaly detection, reconstruction-based methods learn normal patterns for data reconstruction, but often undesirably reconstruct anomalous regions at inferenc…
WeakMCN: Multi-task Collaborative Network for Weakly Supervised Referring Expression Comprehension and Segmentation
Yang Liu, Silin Cheng, Xinwei He +3
Weakly supervised referring expression comprehension(WREC) and segmentation(WRES) aim to learn object grounding based on a given expression using weak supervision signals like imag…
TeDA: Boosting Vision-Lanuage Models for Zero-Shot 3D Object Retrieval via Testing-time Distribution Alignment
Zhichuan Wang, Yang Zhou, Jinhai Xiang +2
Learning discriminative 3D representations that generalize well to unknown testing categories is an emerging requirement for many real-world 3D applications. Existing well-establis…
CLIP-SCGI: Synthesized Caption-Guided Inversion for Person Re-Identification
Qianru Han, Xinwei He, Zhi Liu +3
Person re-identification (ReID) has recently benefited from large pretrained vision-language models such as Contrastive Language-Image Pre-Training (CLIP). However, the absence of…
SimpleFusion: A Simple Fusion Framework for Infrared and Visible Images
Ming Chen, Yuxuan Cheng, Xinwei He +3
Integrating visible and infrared images into one high-quality image, also known as visible and infrared image fusion, is a challenging yet critical task for many downstream vision…