Boundary Detection
89 papers with code • 3 benchmarks • 8 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
Benchmarks
These leaderboards are used to track progress in Boundary Detection
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Libraries
Use these libraries to find Boundary Detection models and implementationsDatasets
Kinetics
NYUv2
PASCAL Context
SoccerNet-v2
CaFFe
Oxford Road Boundaries
Most implemented papers
Holistically-Nested Edge Detection
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
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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
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
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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
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
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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
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ICML 2017
We present Deep Voice, a production-quality text-to-speech system constructed entirely from deep neural networks.
Photo-Sketching: Inferring Contour Drawings from Images
Edges, boundaries and contours are important subjects of study in both computer graphics and computer vision.
Boundary Loss for Remote Sensing Imagery Semantic Segmentation
strivebo/image_segmentation_dl
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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
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This dataset has been used for training the proposed approach as well the state-of-the-art algorithms for comparisons.
