# Ellipse R-CNN: Learning to Infer Elliptical Object from Clustering and Occlusion

arXiv: https://arxiv.org/abs/2001.11584 · HTML: https://mlsanity.com/paper/2001.11584/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Jan 2020.

## Built on by (most cited first, 13 of 13)

- [3D-Aware Ellipse Prediction for Object-Based Camera Pose Estimation](https://mlsanity.com/paper/2105.11494/) (2021)
- [EllipseNet: Anchor-Free Ellipse Detection for Automatic Cardiac Biometrics in Fetal Echocardiography](https://mlsanity.com/paper/2109.12474/) (2021)
- [Perspective-1-Ellipsoid: Formulation, Analysis and Solutions of the Camera Pose Estimation Problem from One Ellipse-Ellipsoid Correspondence](https://mlsanity.com/paper/2208.12513/) (2022)
- [Object-Based Visual Camera Pose Estimation From Ellipsoidal Model and 3D-Aware Ellipse Prediction](https://mlsanity.com/paper/2203.04613/) (2022)
- [Real-Time Ellipse Detection for Robotics Applications](https://mlsanity.com/paper/2102.12670/) (2021)
- [Autonomous Apple Fruitlet Sizing and Growth Rate Tracking using Computer Vision](https://mlsanity.com/paper/2212.01506/) (2022)
- [3D-Aware Object Localization using Gaussian Implicit Occupancy Function](https://mlsanity.com/paper/2303.02058/) (2023)
- [Few-shot Shape Recognition by Learning Deep Shape-aware Features](https://mlsanity.com/paper/2312.01315/) (2023)
- [Streaming Object Detection on Fisheye Cameras for Automatic Parking](https://mlsanity.com/paper/2305.14713/) (2023)
- [CRRS: Concentric Rectangles Regression Strategy for Multi-point Representation on Fisheye Images](https://mlsanity.com/paper/2303.14639/) (2023)
- [A Powerful Face Preprocessing For Robust Kinship Verification based Tensor Analyses](https://mlsanity.com/paper/2312.11290/) (2023)
- [Camera Calibration and Stereo via a Single Image of a Spherical Mirror](https://mlsanity.com/paper/2409.16386/) (2024)
- [Principal Component Analysis for Lunar Crater Detection](https://mlsanity.com/paper/2605.17125/) (2026)

## Abstract (arXiv)

Images of heavily occluded objects in cluttered scenes, such as fruit clusters in trees, are hard to segment. To further retrieve the 3D size and 6D pose of each individual object in such cases, bounding boxes are not reliable from multiple views since only a little portion of the object's geometry is captured. We introduce the first CNN-based ellipse detector, called Ellipse R-CNN, to represent and infer occluded objects as ellipses. We first propose a robust and compact ellipse regression based on the Mask R-CNN architecture for elliptical object detection. Our method can infer the parameters of multiple elliptical objects even they are occluded by other neighboring objects. For better occlusion handling, we exploit refined feature regions for the regression stage, and integrate the U-Net structure for learning different occlusion patterns to compute the final detection score. The correctness of ellipse regression is validated through experiments performed on synthetic data of clustered ellipses. We further quantitatively and qualitatively demonstrate that our approach outperforms the state-of-the-art model (i.e., Mask R-CNN followed by ellipse fitting) and its three variants on both synthetic and real datasets of occluded and clustered elliptical objects.