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
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
Kinetics 400
PASCAL Context
SoccerNet-v2
UruDendro
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.
Deeply supervised salient object detection with short connections
Recent progress on saliency detection is substantial, benefiting mostly from the explosive development of Convolutional Neural Networks (CNNs).
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.
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.
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.
