Topic: "spatial-attention"
chaofengc/Face-SPARNet
Pytorch codes for "Learning Spatial Attention for Face Super-Resolution", TIP 2021.
Language: Python - Size: 7.02 MB - Last synced at: 28 days ago - Pushed at: 2 months ago - Stars: 215 - Forks: 24

alexanderkroner/saliency
Contextual Encoder-Decoder Network for Visual Saliency Prediction [Neural Networks 2020]
Language: Python - Size: 9.75 MB - Last synced at: 21 days ago - Pushed at: 11 months ago - Stars: 191 - Forks: 50

elvisyjlin/SpatialAttentionGAN
SaGAN PyTorch "Generative Adversarial Network with Spatial Attention for Face Attribute Editing"
Language: Python - Size: 118 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 97 - Forks: 20

laugh12321/3D-Attention-Keras
This repo contains the 3D implementation of the commonly used attention mechanism for imaging.
Language: Python - Size: 126 KB - Last synced at: 22 days ago - Pushed at: over 2 years ago - Stars: 46 - Forks: 12

aimerykong/Pixel-Attentional-Gating
Pixel Attentional Gating for Parsimonious Per-Pixel Labeling
Language: Matlab - Size: 14.3 MB - Last synced at: over 1 year ago - Pushed at: over 6 years ago - Stars: 45 - Forks: 8

tchittesh/lzu
Code for Learning to Zoom and Unzoom (CVPR 2023)
Language: Python - Size: 35.3 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 38 - Forks: 4

MaitreChen/MedGAN-ResLite
一个用于肺炎图像分类的轻量级ResNet18-SAM模型实现,采用SH-DCGAN生成少类样本数据,解决了数据不平衡的问题,同时结合剪枝策略实现轻量化!MedGAN-ResLite-V2 Released! Stay tuned!❤
Language: Python - Size: 40.8 MB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 19 - Forks: 1

zouguojian/Traffic-flow-prediction
This work considers combine multi-tricks with highway network to achieve traffic flow prediction accurately.
Language: Python - Size: 452 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 13 - Forks: 3

billymoonxd/ResUNet
Medical Image Segmentation using Residual U-Net with Attention Mechanisms.
Language: Python - Size: 48.1 MB - Last synced at: almost 2 years ago - Pushed at: almost 3 years ago - Stars: 10 - Forks: 1

mohamedac29/DSANet
DSANet: Dilated Spatial Attention for Real-time Semantic Segmentation in Urban Street Scenes
Language: Python - Size: 16.9 MB - Last synced at: about 2 years ago - Pushed at: almost 3 years ago - Stars: 8 - Forks: 1

arangesh/Forced-Spatial-Attention
Akshay Rangesh and Mohan Trivedi, "Forced Spatial Attention for Driver Foot Activity Classification," ICCV Workshop on Assistive Computer Vision and Robotics, 2019.
Language: Python - Size: 15.5 MB - Last synced at: about 2 years ago - Pushed at: about 5 years ago - Stars: 6 - Forks: 0

maklachur/SCSAtt
Efficient Visual Tracking with Stacked Channel-Spatial Attention Learning
Language: Python - Size: 17.1 MB - Last synced at: over 1 year ago - Pushed at: almost 2 years ago - Stars: 3 - Forks: 0

sabrid369/BFMD-SN-U-net
The open source code for the paper "Block Attention and Switchable Normalization based Deep Learning Framework for Segmentation of Retinal Vessels"
Language: Python - Size: 110 KB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 2 - Forks: 1

catsaveearth/Hint-based-Image-Colorization-Using-HSCAU-Net
Hint based Image Colorization ConvNet Challenge 2022 in Computer Vision from Prof. YJ Jung in Gachon Univ
Language: Python - Size: 11.7 KB - Last synced at: about 2 years ago - Pushed at: almost 3 years ago - Stars: 1 - Forks: 0

alizindari/Bifurcated-Auto-Encoder
A bifurcated auto-encoder based on channel-wise and spatial-wise attention mechanism with synthetically generated data for segmentation of covid-19 infected regions in CT images
Language: Jupyter Notebook - Size: 419 KB - Last synced at: over 1 year ago - Pushed at: over 3 years ago - Stars: 1 - Forks: 0

fardinafdideh/Invasive-cognitive-brain-computer-interfaces-to-enhance-and-restore-attention
Invasive Cognitive Brain-computer Interfaces to Enhance and Restore Attention: Non-human Primates Study
Size: 354 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0
