Boundary Detection

64 papers with code • 3 benchmarks • 7 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


Use these libraries to find Boundary Detection models and implementations

Most implemented papers

Holistically-Nested Edge Detection

s9xie/hed ICCV 2015

We develop a new edge detection algorithm that tackles two important issues in this long-standing vision problem: (1) holistic image training and prediction; and (2) multi-scale and multi-level feature learning.

Ridiculously Fast Shot Boundary Detection with Fully Convolutional Neural Networks

Tangshitao/ClipShots_basline 23 May 2017

Shot boundary detection (SBD) is an important component of many video analysis tasks, such as action recognition, video indexing, summarization and editing.

Large-scale, Fast and Accurate Shot Boundary Detection through Spatio-temporal Convolutional Neural Networks

melgharib/DSBD 9 May 2017

Since current datasets are not large enough to train an accurate SBD CNN, we present a new dataset containing more than 3. 5 million frames of sharp and gradual transitions.

TransNet: A deep network for fast detection of common shot transitions

soCzech/TransNet 8 Jun 2019

Shot boundary detection (SBD) is an important first step in many video processing applications.

TransNet V2: An effective deep network architecture for fast shot transition detection

soCzech/TransNetV2 11 Aug 2020

Although automatic shot transition detection approaches are already investigated for more than two decades, an effective universal human-level model was not proposed yet.

Flood-Filling Networks

google/ffn 1 Nov 2016

State-of-the-art image segmentation algorithms generally consist of at least two successive and distinct computations: a boundary detection process that uses local image information to classify image locations as boundaries between objects, followed by a pixel grouping step such as watershed or connected components that clusters pixels into segments.

Deep Voice: Real-time Neural Text-to-Speech

NVIDIA/nv-wavenet ICML 2017

We present Deep Voice, a production-quality text-to-speech system constructed entirely from deep neural networks.

Boundary Loss for Remote Sensing Imagery Semantic Segmentation

strivebo/image_segmentation_dl 20 May 2019

Convolutional neural networks are powerful visual models that yield hierarchies of features and practitioners widely use them to process remote sensing data.

Dense Extreme Inception Network: Towards a Robust CNN Model for Edge Detection

xavysp/DexiNed 4 Sep 2019

This dataset has been used for training the proposed approach as well the state-of-the-art algorithms for comparisons.

Recursive Training of 2D-3D Convolutional Networks for Neuronal Boundary Detection

seung-lab/znn-release NeurIPS 2015

Efforts to automate the reconstruction of neural circuits from 3D electron microscopic (EM) brain images are critical for the field of connectomics.