A Neuromorphic Dataset for Object Segmentation in Indoor Cluttered Environment

2023-02-13 · Xiaoqian Huang, Kachole Sanket, Abdulla Ayyad, Fariborz Baghaei Naeini, Dimitrios Makris, Yahya Zweiri

Taking advantage of an event-based camera, the issues of motion blur, low dynamic range and low time sampling of standard cameras can all be addressed. However, there is a lack of event-based datasets dedicated to the benchmarking of segmentation algorithms, especially those that provide depth information which is critical for segmentation in occluded scenes. This paper proposes a new Event-based Segmentation Dataset (ESD), a high-quality 3D spatial and temporal dataset for object segmentation in an indoor cluttered environment. Our proposed dataset ESD comprises 145 sequences with 14,166 RGB frames that are manually annotated with instance masks. Overall 21.88 million and 20.80 million events from two event-based cameras in a stereo-graphic configuration are collected, respectively. To the best of our knowledge, this densely annotated and 3D spatial-temporal event-based segmentation benchmark of tabletop objects is the first of its kind. By releasing ESD, we expect to provide the community with a challenging segmentation benchmark with high quality.

📄 PDF Abstract BibTeX arXiv:2302.06301

Code (1)

yellow07200/ESD_labeling_tool 공식 구현

Tasks

Benchmarking Segmentation Semantic Segmentation

SupeRGB-D: Zero-shot Instance Segmentation in Cluttered Indoor Environments

2022-12-22 · Evin Pınar Örnek, Aravindhan K Krishnan, Shreekant Gayaka, Cheng-Hao Kuo 외

Object instance segmentation is a key challenge for indoor robots navigating cluttered environments with many small objects. Limitations in 3D sensing capabilities often make it difficult to detect every possible object.…

Instance Segmentation Object Semantic Segmentation Zero-Shot Instance Segmentation

Semantic Instance Labeling Leveraging Hierarchical Segmentation

2017-08-02 · Steven Hickson, Irfan Essa, Henrik Christensen

Most of the approaches for indoor RGBD semantic la- beling focus on using pixels or superpixels to train a classi- fier. In this paper, we implement a higher level segmentation using a hierarchy of superpixels to obtain …

Segmentation Superpixels

Perceptual Organization and Recognition of Indoor Scenes from RGB-D Images

2013-06-01 · CVPR 2013 6 · Saurabh Gupta, Pablo Arbelaez, Jitendra Malik

We address the problems of contour detection, bottomup grouping and semantic segmentation using RGB-D data. We focus on the challenging setting of cluttered indoor scenes, and evaluate our approach on the recently introd…

Boundary Detection Contour Detection Object Object Recognition+4

Depth-guided Free-space Segmentation for a Mobile Robot

2023-11-03 · Christos Sevastopoulos, Joey Hussain, Stasinos Konstantopoulos, Vangelis Karkaletsis 외

Accurate indoor free-space segmentation is a challenging task due to the complexity and the dynamic nature that indoor environments exhibit. We propose an indoors free-space segmentation method that associates large dept…

Segmentation Superpixels

UnScene3D: Unsupervised 3D Instance Segmentation for Indoor Scenes

2023-03-25 · CVPR 2024 1 · David Rozenberszki, Or Litany, Angela Dai

3D instance segmentation is fundamental to geometric understanding of the world around us. Existing methods for instance segmentation of 3D scenes rely on supervision from expensive, manual 3D annotations. We propose UnS…

3D Instance Segmentation Instance Segmentation Segmentation Semantic Segmentation