Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
Bottom Up Attention | 979 | 3 years ago | 56 | mit | Jupyter Notebook | |||||
Bottom-up attention model for image captioning and VQA, based on Faster R-CNN and Visual Genome | ||||||||||
Cgnl Network.pytorch | 253 | 3 years ago | 1 | mit | Python | |||||
Compact Generalized Non-local Network (NIPS 2018) | ||||||||||
Sstd | 222 | 6 years ago | 3 | other | C++ | |||||
Single Shot Text Detector with Regional Attention | ||||||||||
Up Down Captioner | 218 | 5 years ago | 17 | mit | Jupyter Notebook | |||||
Automatic image captioning model based on Caffe, using features from bottom-up attention. | ||||||||||
Ags | 209 | a year ago | 2 | Python | ||||||
Learning Unsupervised Video Object Segmentation through Visual Attention (CVPR19, PAMI20) | ||||||||||
Bottom Up Attention.pytorch | 207 | 2 years ago | 2 | apache-2.0 | Jupyter Notebook | |||||
A PyTorch reimplementation of bottom-up-attention models | ||||||||||
Mgcam | 91 | 6 years ago | 4 | Python | ||||||
Mask data and code for 'Mask-guided Contrastive Attention Model for Person Re-Identification' (CVPR-2018) | ||||||||||
Opam_tip2018 | 80 | 5 years ago | 10 | Jupyter Notebook | ||||||
Source code of our TIP 2018 paper "Object-Part Attention Model for Fine-grained Image Classification" | ||||||||||
Jaanet | 76 | 4 years ago | C++ | |||||||
ECCV 2018 "Deep Adaptive Attention for Joint Facial Action Unit Detection and Face Alignment" | ||||||||||
Deepattention | 55 | 5 years ago | MATLAB | |||||||
Deep Visual Attention Prediction (TIP18) |