1k citations · 1.8k across the 9 of their papers we have counts for
7 papers · 1 filter
PointRend: Image Segmentation as Rendering
Alexander Kirillov, Yuxin Wu, Kaiming He +1
We present a new method for efficient high-quality image segmentation of objects and scenes. By analogizing classical computer graphics methods for efficient rendering with over- a…
A Multigrid Method for Efficiently Training Video Models
Chao-Yuan Wu, Ross Girshick, Kaiming He +2
Training competitive deep video models is an order of magnitude slower than training their counterpart image models. Slow training causes long research cycles, which hinders progre…
Momentum Contrast for Unsupervised Visual Representation Learning
Kaiming He, Haoqi Fan, Yuxin Wu +2
We present Momentum Contrast (MoCo) for unsupervised visual representation learning. From a perspective on contrastive learning as dictionary look-up, we build a dynamic dictionary…
Exploring Randomly Wired Neural Networks for Image Recognition
Saining Xie, Alexander Kirillov, Ross Girshick +1
Neural networks for image recognition have evolved through extensive manual design from simple chain-like models to structures with multiple wiring paths. The success of ResNets an…
Deep Hough Voting for 3D Object Detection in Point Clouds
Charles R. Qi, Or Litany, Kaiming He +1
Current 3D object detection methods are heavily influenced by 2D detectors. In order to leverage architectures in 2D detectors, they often convert 3D point clouds to regular grids…
TensorMask: A Foundation for Dense Object Segmentation
Xinlei Chen, Ross Girshick, Kaiming He +1
Sliding-window object detectors that generate bounding-box object predictions over a dense, regular grid have advanced rapidly and proven popular. In contrast, modern instance segm…