562 citations · 619 across the 8 of their papers we have counts for
5 papers · 1 filter
Pointly-Supervised Instance Segmentation
Bowen Cheng, Omkar Parkhi, Alexander Kirillov
We propose an embarrassingly simple point annotation scheme to collect weak supervision for instance segmentation. In addition to bounding boxes, we collect binary labels for a set…
Boundary IoU: Improving Object-Centric Image Segmentation Evaluation
Bowen Cheng, Ross Girshick, Piotr Dollár +2
We present Boundary IoU (Intersection-over-Union), a new segmentation evaluation measure focused on boundary quality. We perform an extensive analysis across different error types…
On Interaction Between Augmentations and Corruptions in Natural Corruption Robustness
Eric Mintun, Alexander Kirillov, Saining Xie
Invariance to a broad array of image corruptions, such as warping, noise, or color shifts, is an important aspect of building robust models in computer vision. Recently, several ne…
Evaluating Large-Vocabulary Object Detectors: The Devil is in the Details
Achal Dave, Piotr Dollár, Deva Ramanan +2
By design, average precision (AP) for object detection aims to treat all classes independently: AP is computed independently per category and averaged. On one hand, this is desirab…
TrackFormer: Multi-Object Tracking with Transformers
Tim Meinhardt, Alexander Kirillov, Laura Leal-Taixe +1
The challenging task of multi-object tracking (MOT) requires simultaneous reasoning about track initialization, identity, and spatio-temporal trajectories. We formulate this task a…