2 citations · 7 across the 10 of their papers we have counts for
11 papers
ASBench: Image Anomalies Synthesis Benchmark for Anomaly Detection
Qunyi Zhang, Songan Zhang, Jiaqi Liu +5
Anomaly detection plays a pivotal role in manufacturing quality control, yet its application is constrained by limited abnormal samples and high manual annotation costs. While anom…
STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment
Xichen Xu, Yanshu Wang, Jinbao Wang +5
Segmentation-oriented Industrial Anomaly Synthesis (SIAS) plays a pivotal role in enhancing the performance of downstream anomaly segmentation, as it provides an effective means of…
FAST: Foreground-aware Diffusion with Accelerated Sampling Trajectory for Segmentation-oriented Anomaly Synthesis
Xichen Xu, Yanshu Wang, Jinbao Wang +4
Industrial anomaly segmentation relies heavily on pixel-level annotations, yet real-world anomalies are often scarce, diverse, and costly to label. Segmentation-oriented industrial…
Trade-offs in Image Generation: How Do Different Dimensions Interact?
Sicheng Zhang, Binzhu Xie, Zhonghao Yan +7
Model performance in text-to-image (T2I) and image-to-image (I2I) generation often depends on multiple aspects, including quality, alignment, diversity, and robustness. However, mo…
Learning from Loss Landscape: Generalizable Mixed-Precision Quantization via Adaptive Sharpness-Aware Gradient Aligning
Lianbo Ma, Jianlun Ma, Yuee Zhou +3
Mixed Precision Quantization (MPQ) has become an essential technique for optimizing neural network by determining the optimal bitwidth per layer. Existing MPQ methods, however, fac…
A Survey on Industrial Anomaly Synthesis
Yanshu Wang, Xichen Xu, Jiaqi Liu +6
This paper presents a comprehensive review of industrial anomaly synthesis (IAS). Existing surveys on industrial anomalies mainly focus on anomaly detection, while IAS is typically…
Revisiting Multimodal Fusion for 3D Anomaly Detection from an Architectural Perspective
Kaifang Long, Guoyang Xie, Lianbo Ma +2
Existing efforts to boost multimodal fusion of 3D anomaly detection (3D-AD) primarily concentrate on devising more effective multimodal fusion strategies. However, little attention…
Towards Zero-shot Point Cloud Anomaly Detection: A Multi-View Projection Framework
Yuqi Cheng, Yunkang Cao, Guoyang Xie +2
Detecting anomalies within point clouds is crucial for various industrial applications, but traditional unsupervised methods face challenges due to data acquisition costs, early-st…
Rethinking Unsupervised Outlier Detection via Multiple Thresholding
Zhonghang Liu, Panzhong Lu, Guoyang Xie +2
In the realm of unsupervised image outlier detection, assigning outlier scores holds greater significance than its subsequent task: thresholding for predicting labels. This is beca…
AnomalyXFusion: Multi-modal Anomaly Synthesis with Diffusion
Jie Hu, Yawen Huang, Yilin Lu +4
Anomaly synthesis is one of the effective methods to augment abnormal samples for training. However, current anomaly synthesis methods predominantly rely on texture information as…
ShadowMaskFormer: Mask Augmented Patch Embeddings for Shadow Removal
Zhuohao Li, Guoyang Xie, Guannan Jiang +1
Transformer recently emerged as the de facto model for computer vision tasks and has also been successfully applied to shadow removal. However, these existing methods heavily rely…