Salient object detectionSaliency detectionMulti-scale featuresBoundaryAttentionBenefiting from the development of convolutional neural networks, salient object detection has achieved prominent progress in recent
To address these issues, we propose a multi-scale deep encoder-decoder network (dubbed DEDN) for salient object detection, which contains two parallel streams to locate object regions at different scales and a convolutional layer to merge the multi-scale features. A main motivation behind this de...
【TMM2024】Frequency-Guided Spatial Adaptation for Camouflaged Object Detection 论文链接: https://arxiv.org/abs/2409.12421这个论文研究 Camouflaged Object Detection (COD)问题,作者认为,使用 pretrained foundation model 可以改进COD的准确率,但是当前的 ada… 高峰OUC发表于OUC的搬... MULTI-SCALE CONTEXT AGGRE...
1.论文信息 标题:Multi-scale Interactive Network for Salient Object Detection 显著性目标检测,多尺度信息相互融合 机构:大连理工大学/鹏城实验室 会议:CVPR2020 推理速度:35FPS 阅读时间:2020/02/27 数…
1、Lightweight Multi-Scale Adapter,LMSA 作者认为,SAM编码器的参数过多,同时 SOD训练数据不足会影响网络的全面微调,因此,使用Adaptor可以让SAM应用于SOD,同时,应用多尺度特征提取能够提升性能。LMSA结构如下图所示,本质上就是在 Adpator 里把特征池化成多个尺度分别处理。
Multi-scale Interactive Network for Salient Object Detection CVPR20 摘要 本文提出MINet。在编码器中使用聚合交互模块AIM(aggregate interaction modules)来聚合相邻level的特征,由于仅使用小的up/down采样率,引入了很少噪声。在解码器中使用自交互模型SIM(self-interaction module)来利用multi-scale特征。
cGAN-based architecture: The model utilizes a cGAN that consists of two distinct subnetworks: one dedicated to image dehazing using advanced techniques such as residual blocks, Dark Channel Prior, total variation, and multiscale Retinex algorithm, and another for salient object detection, enhanced by...
Multi-scale Interactive Network for Salient Object Detection CVPR 2020. NONE: For subsequent updates of the paper, please see the arixv version. Changelog The code and experimental results have be released now 😄. 2021/6/6: Move the script cal_fps.py into the folder tools. Add a script...
Recent CNNs based salient object detection approaches tend to embed a fully connected Conditional Random Field (CRF) layer to refine the saliency maps from CNNs for post processing. Due to the significant performance enhancement by the CRF layer, in this
Camouflaged object detection (COD) is significantly more challenging than traditional salient object detection (SOD) due to the high intrinsic similarity between camouflaged objects and their backgrounds, as well as complex environmental conditions. Although current deep learning methods have achieved remarkab...