Distorted Representation Space Characterization Through Backpropagated Gradients

Backpropagated Gradient Representations for Anomaly Detection

Learning representations that clearly distinguish between normal and abnormal data is key to the success of anomaly detection. Most of existing anomaly detection algorithms use activation representations from forward propagation while not exploiting gradients from backpropagation to characterize data. Gradients capture model updates required to represent data. Anomalies require more drastic model updates to fully represent them compared to normal data. Hence, we propose the utilization of backpropagated gradients as representations to characterize model behavior on anomalies and, consequently,…

梯度幅值相似度偏差：一种高效的感知图像质量指标

Gradient Magnitude Similarity Deviation: A Highly Efficient Perceptual Image Quality Index

针对图像质量评估需兼顾精度与效率的需求，提出基于梯度幅值相似度图标准差的GMSD算法，兼具高预测精度与极低计算成本。

Image Quality Assessment with Gradient Siamese Network

In this work, we introduce Gradient Siamese Network (GSN) for image quality assessment. The proposed method is skilled in capturing the gradient features between distorted images and reference images in full-reference image quality assessment(IQA) task. We utilize Central Differential Convolution to obtain both semantic features and detail difference hidden in image pair. Furthermore, spatial attention guides the network to concentrate on regions related to image detail. For the low-level, mid-level and high-level features extracted by the network, we innovatively design a multi-level fusion m…

A Shift-insensitive Full Reference Image Quality Assessment Model Based on Quadratic Sum of Gradient Magnitude and LOG signals

Image quality assessment that aims at estimating the subject quality of images, builds models to evaluate the perceptual quality of the image in different applications. Based on the fact that the human visual system (HVS) is highly sensitive to structural information, the edge information extraction is widely applied in different IQA metrics. According to previous studies, the image gradient magnitude (GM) and the Laplacian of Gaussian (LOG) operator are two efficient structural features in IQA tasks. However, most of the IQA metrics achieve good performance only when the distorted image is to…

Fuse4Seg: 多模态医学分割的图像融合 via 两级优化

Fuse4Seg: Image Fusion for Multi-Modal Medical Segmentation via Bi-level Optimization

Fuse4Seg通过两级优化实现多模态医学图像融合，解决视觉与语义间的差距问题，提升分割任务的准确性和临床可解释性。

从失真关系视角审视小样本真实图像超分辨率

A Close Look at Few-shot Real Image Super-resolution from the Distortion Relation Perspective

本文首次提出小样本真实图像超分辨率场景，并设计失真关系引导的迁移学习方法DRTL，通过知识图谱和梯度重加权从合成失真中迁移相关知识，在预训练和元学习框架下显著提升了少样本RealSR性能。