Boundary Detection
99 papers with code • 3 benchmarks • 10 datasets
Boundary Detection is a vital part of extracting information encoded in images, allowing for the computation of quantities of interest including density, velocity, pressure, etc.
Source: A Locally Adapting Technique for Boundary Detection using Image Segmentation
Libraries
Use these libraries to find Boundary Detection models and implementationsDatasets
Most implemented papers
Dense Extreme Inception Network: Towards a Robust CNN Model for Edge Detection
This dataset has been used for training the proposed approach as well the state-of-the-art algorithms for comparisons.
SoccerNet-v2: A Dataset and Benchmarks for Holistic Understanding of Broadcast Soccer Videos
In this work, we propose SoccerNet-v2, a novel large-scale corpus of manual annotations for the SoccerNet video dataset, along with open challenges to encourage more research in soccer understanding and broadcast production.
Progressive Attention on Multi-Level Dense Difference Maps for Generic Event Boundary Detection
Generic event boundary detection is an important yet challenging task in video understanding, which aims at detecting the moments where humans naturally perceive event boundaries.
Recursive Training of 2D-3D Convolutional Networks for Neuronal Boundary Detection
Efforts to automate the reconstruction of neural circuits from 3D electron microscopic (EM) brain images are critical for the field of connectomics.
Convolutional Oriented Boundaries: From Image Segmentation to High-Level Tasks
We present Convolutional Oriented Boundaries (COB), which produces multiscale oriented contours and region hierarchies starting from generic image classification Convolutional Neural Networks (CNNs).
Recurrent Pixel Embedding for Instance Grouping
We introduce a differentiable, end-to-end trainable framework for solving pixel-level grouping problems such as instance segmentation consisting of two novel components.
Self-Supervised Contrastive Learning for Unsupervised Phoneme Segmentation
Results suggest that our approach surpasses the baseline models and reaches state-of-the-art performance on both data sets.
Music Boundary Detection using Convolutional Neural Networks: A comparative analysis of combined input features
The objective of this work is to establish a general method of pre-processing these inputs by comparing the inputs calculated from different pooling strategies, distance metrics and audio characteristics, also taking into account the computing time to obtain them.
Generic Event Boundary Detection: A Benchmark for Event Segmentation
This paper presents a novel task together with a new benchmark for detecting generic, taxonomy-free event boundaries that segment a whole video into chunks.
Weakly Supervised Named Entity Tagging with Learnable Logical Rules
We study the problem of building entity tagging systems by using a few rules as weak supervision.