Ross B. Girshick
- Publications
- Influence
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IEEE Transactions on Pattern Analysis and Machine…
State-of-the-art object detection networks depend on region proposal algorithms to hypothesize object locations. Advances like SPPnet and Fast R-CNN have reduced the running time of these detection… Continue Reading
IEEE International Conference on Computer Vision…
This paper proposes a Fast Region-based Convolutional Network method (Fast R-CNN) for object detection. Fast R-CNN builds on previous work to efficiently classify object proposals using deep… Continue Reading
IEEE Conference on Computer Vision and Pattern…
Object detection performance, as measured on the canonical PASCAL VOC dataset, has plateaued in the last few years. The best-performing methods are complex ensemble systems that typically combine… Continue Reading
IEEE Transactions on Pattern Analysis and Machine…
We describe an object detection system based on mixtures of multiscale deformable part models. Our system is able to represent highly variable object classes and achieves state-of-the-art results in… Continue Reading
Caffe provides multimedia scientists and practitioners with a clean and modifiable framework for state-of-the-art deep learning algorithms and a collection of reference models. The framework is a… Continue Reading
IEEE Conference on Computer Vision and Pattern…
We present YOLO, a new approach to object detection. Prior work on object detection repurposes classifiers to perform detection. Instead, we frame object detection as a regression problem to… Continue Reading
IEEE Conference on Computer Vision and Pattern…
Feature pyramids are a basic component in recognition systems for detecting objects at different scales. But pyramid representations have been avoided in recent object detectors that are based on… Continue Reading
IEEE International Conference on Computer Vision…
We present a conceptually simple, flexible, and general framework for object instance segmentation. Our approach efficiently detects objects in an image while simultaneously generating a high-quality… Continue Reading
IEEE Transactions on Pattern Analysis and Machine…
We present a conceptually simple, flexible, and general framework for object instance segmentation. Our approach efficiently detects objects in an image while simultaneously generating a high-quality… Continue Reading
IEEE Conference on Computer Vision and Pattern…
We present a simple, highly modularized network architecture for image classification. Our network is constructed by repeating a building block that aggregates a set of transformations with the same… Continue Reading