167 citations · 312 across the 5 of their papers we have counts for
7 papers
Point-Level Region Contrast for Object Detection Pre-Training
Yutong Bai, Xinlei Chen, Alexander Kirillov +2
In this work we present point-level region contrast, a self-supervised pre-training approach for the task of object detection. This approach is motivated by the two key factors in…
Per-Pixel Classification is Not All You Need for Semantic Segmentation
Bowen Cheng, Alexander G. Schwing, Alexander Kirillov
Modern approaches typically formulate semantic segmentation as a per-pixel classification task, while instance-level segmentation is handled with an alternative mask classification…
End-to-End Object Detection with Transformers
Nicolas Carion, Francisco Massa, Gabriel Synnaeve +3
We present a new method that views object detection as a direct set prediction problem. Our approach streamlines the detection pipeline, effectively removing the need for many hand…
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…
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…
Panoptic Feature Pyramid Networks
Alexander Kirillov, Ross Girshick, Kaiming He +1
The recently introduced panoptic segmentation task has renewed our community's interest in unifying the tasks of instance segmentation (for thing classes) and semantic segmentation…