vision: 44 curated resources
vision
44 resources · page 2 of 2
Faster R-CNN
by Shaoqing Ren et al. (Microsoft Research)
NeurIPS paper (PDF, 2015) Faster R-CNN: real-time object detection with region proposal networks.
Inception / GoogLeNet
by Christian Szegedy et al. (Google)
arXiv PDF of the GoogLeNet paper (2014) introducing the Inception architecture.
Mask R-CNN
by Kaiming He et al. (Facebook AI Research)
arXiv paper (2017) "Mask R-CNN", introducing Mask R-CNN for instance segmentation.
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
by Andrew G. Howard et al. (Google)
arXiv PDF of the MobileNets paper (2017) on efficient convolutional networks for mobile vision.
Moirai
by Gerald Woo et al. (Salesforce)
arXiv PDF of the Moirai paper (2024), Salesforce's universal time-series forecasting transformer.
ResNet
by Kaiming He et al. (Microsoft)
arXiv paper (2015) "Deep Residual Learning for Image Recognition", introducing ResNet residual networks.
SAM
by Alexander Kirillov et al. (Meta AI)
arXiv paper (2023) introducing Segment Anything (SAM), a promptable image segmentation model and dataset.
A decoder-only foundation model for time-series forecasting (TimesFM)
by Abhimanyu Das et al. (Google)
arXiv paper (2023) introducing TimesFM, a decoder-only foundation model for time-series forecasting.
U-Net
by Olaf Ronneberger et al. (University of Freiburg)
arXiv paper (2015) "U-Net: Convolutional Networks for Biomedical Image Segmentation", introducing the encoder-decoder architecture with skip connections.
VGG
by Karen Simonyan and Andrew Zisserman (University of Oxford)
arXiv PDF of the VGG paper (2014) on very deep convolutional networks for large-scale image recognition.
ViT
by Alexey Dosovitskiy et al. (Google)
arXiv paper (2020) introducing the Vision Transformer (ViT) for image recognition.
YOLO
by Joseph Redmon et al. (University of Washington)
arXiv paper (2015) "You Only Look Once: Unified, Real-Time Object Detection", introducing YOLO, a single-stage real-time object detector.