Deep Learning: Segmentation and Object Detection

In this paper, we propose a new way to generate object proposals, introducing an approach based on a discriminative convolutional network.

The top branch predicts a segmentation mask for the the object located at the center while the bottom branch predicts an object score for the input patch. ( ...

Recent object detection systems rely on two critical steps: (1) a set of object proposals is predicted as efficiently as possible, and (2) this set of ...

In this paper, we present a simple yet effective approach for segmenting object proposals via a deep architecture of recursive neural networks ( ...

In this paper, we propose a new way to generate object proposals, introducing an approach based on a discriminative convolutional network.

In this paper, we propose a new way to generate object proposals, introducing an approach based on a discriminative convolutional network.

Recent object detection systems rely on two critical steps: (1) a set of object proposals is predicted as efficiently as possible, and (2) this set of ...

Use deep networks to answer each yes/no question. • Networks (and computation) shared for every patch and every pixel to segment all the objects in an image.

The key idea is to build a tree structure that could progressively learn fine-grained features to distinguish a subset of classes, by learning features only ...

A new way to generate object proposals is proposed, introducing an approach based on a discriminative convolutional network that obtains substantially ...