About

Edge Detection is a fundamental image processing technique which involves computing an image gradient to quantify the magnitude and direction of edges in an image. Image gradients are used in various downstream tasks in computer vision such as line detection, feature detection, and image classification.

Source: Artistic Enhancement and Style Transfer of Image Edges using Directional Pseudo-coloring

Benchmarks

TREND DATASET BEST METHOD PAPER TITLE PAPER CODE COMPARE

Datasets

Greatest papers with code

Holistically-Nested Edge Detection

ICCV 2015 tensorpack/tensorpack

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.

BOUNDARY DETECTION EDGE DETECTION

A survey on Kornia: an Open Source Differentiable Computer Vision Library for PyTorch

21 Sep 2020kornia/kornia

This work presents Kornia, an open source computer vision library built upon a set of differentiable routines and modules that aims to solve generic computer vision problems.

EDGE DETECTION

Kornia: an Open Source Differentiable Computer Vision Library for PyTorch

5 Oct 2019kornia/kornia

This work presents Kornia -- an open source computer vision library which consists of a set of differentiable routines and modules to solve generic computer vision problems.

EDGE DETECTION IMAGE AUGMENTATION IMAGE CROPPING IMAGE DENOISING IMAGE MANIPULATION IMAGE MORPHING IMAGE RETRIEVAL IMAGE SMOOTHING IMAGE STITCHING

Richer Convolutional Features for Edge Detection

CVPR 2017 yun-liu/rcf

Using VGG16 network, we achieve \sArt results on several available datasets.

BSDS500 EDGE DETECTION

Instance-level Human Parsing via Part Grouping Network

ECCV 2018 Engineering-Course/CIHP_PGN

Instance-level human parsing towards real-world human analysis scenarios is still under-explored due to the absence of sufficient data resources and technical difficulty in parsing multiple instances in a single pass.

EDGE DETECTION HUMAN PARSING HUMAN PART SEGMENTATION REPRESENTATION LEARNING

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

4 Sep 2019xavysp/DexiNed

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

BOUNDARY DETECTION EDGE DETECTION

Bi-Directional Cascade Network for Perceptual Edge Detection

CVPR 2019 pkuCactus/BDCN

Exploiting multi-scale representations is critical to improve edge detection for objects at different scales.

BSDS500 EDGE DETECTION

Dynamic Feature Fusion for Semantic Edge Detection

25 Feb 2019Lavender105/DFF

In this work, we propose a novel dynamic feature fusion strategy that assigns different fusion weights for different input images and locations adaptively.

EDGE DETECTION

CASENet: Deep Category-Aware Semantic Edge Detection

CVPR 2017 Lavender105/DFF

To this end, we propose a novel end-to-end deep semantic edge learning architecture based on ResNet and a new skip-layer architecture where category-wise edge activations at the top convolution layer share and are fused with the same set of bottom layer features.

EDGE DETECTION OBJECT PROPOSAL GENERATION SEMANTIC SEGMENTATION

Feature Pyramid and Hierarchical Boosting Network for Pavement Crack Detection

18 Jan 2019fyangneil/pavement-crack-detection

To demonstrate the superiority and generality of the proposed method, we evaluate the proposed method on five crack datasets and compare it with state-of-the-art crack detection, edge detection, semantic segmentation methods.

EDGE DETECTION SEMANTIC SEGMENTATION