Apr 16, 2019 · We model an object as a single point --- the center point of its bounding box. Our detector uses keypoint estimation to find center points and regresses to all ...

Our detector uses keypoint estimation to find center points and regresses to all other object properties, such as size, 3D location, orientation, and even pose.

This work presents a conceptually simple, flexible, and general framework for object instance segmentation, which extends Faster R-CNN.

Oct 25, 2022 · A deep learning-based object detection method that uses pre-defined bounding boxes (anchors) as proposals is known as anchor-based object detection.

May 9, 2020 · CenterNet: Objects as Points¹ proposes a fast, simple, and accurate method for predicting the bounding boxes and poses of objects and persons ...

2D/3D Object Detection and Pose Estimation. Contribute to borhanMorphy/object-as-points development by creating an account on GitHub.

Abstract. Tracking has traditionally been the art of following interest points through space and time. This changed with the rise of powerful deep networks.

Our detector uses keypoint estimation to find center points and regresses to all other object properties, such as size, 3D location, orientation, and even pose.

Tracking has traditionally been the art of following interest points through space and time. This changed with the rise of powerful deep networks.

In this paper, we present a simultaneous detection and tracking algorithm that is simpler, faster, and more accurate than the state of the art. Our tracker, ...