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Edge Detection

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하위 태스크: 0
평가표: 8
보존된 평가 기록: 27

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

( Image credit: Kornia )

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/li-yachuan/edmb

공식 코드

EDMB: Edge Detector with Mamba

https://github.com/li-yachuan/nbed

공식 코드

A new baseline for edge detection: Make Encoder-Decoder great again

https://github.com/lktidaohuoxing/superedge

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SuperEdge: Towards a Generalization Model for Self-Supervised Edge Detection

https://github.com/martianxiu/MSECNet

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MSECNet: Accurate and Robust Normal Estimation for 3D Point Clouds by Multi-Scale Edge Conditioning

https://github.com/matej-ulicny/harmonic-networks

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Harmonic Convolutional Networks based on Discrete Cosine Transform

https://github.com/mengyangpu/edter

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EDTER: Edge Detection with Transformer

https://github.com/mikeadamer/mag-metric

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The magnitude vector of images

https://github.com/nachifur/LLPC

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Local Label Point Correction for Edge Detection of Overlapping Cervical Cells

https://github.com/nailperry-zd/paddleseg-trianglenet

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TriangleNet: Edge Prior Augmented Network for Semantic Segmentation through Cross-Task Consistency

https://github.com/nikosefth/im2rbte

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Edge Augmentation for Large-Scale Sketch Recognition without Sketches

https://github.com/oranshayer/BRRF

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Enhancing Generic Segmentation with Learned Region Representations

https://github.com/ostadabbas/SPAC-Net-Synthetic-Pose-aware-Animal-ControlNet

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SPAC-Net: Synthetic Pose-aware Animal ControlNet for Enhanced Pose Estimation

https://github.com/pkuCactus/BDCN

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Bi-Directional Cascade Network for Perceptual Edge Detection

https://github.com/quickhdsdc/Point-Tracking-for-Displacement-Measurement-in-Railway-Applications

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Deep Learning based Virtual Point Tracking for Real-Time Target-less Dynamic Displacement Measurement in Railway Applications

https://github.com/ranaa-b/OOCS

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On-Off Center-Surround Receptive Fields for Accurate and Robust Image Classification

https://github.com/rashaalshawi/dual-attention-u-net-with-feature-infusion-pushing-the-boundaries-of-multiclass-defect-segmentation

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Dual Attention U-Net with Feature Infusion: Pushing the Boundaries of Multiclass Defect Segmentation

https://github.com/raymondyeh07/tv_layers_for_cv

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Total Variation Optimization Layers for Computer Vision

https://github.com/ricupa/mtml-learn-how-to-adapt-to-unseen-tasks

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Multi-Task Meta Learning: learn how to adapt to unseen tasks

https://github.com/s9xie/hed

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Holistically-Nested Edge Detection

https://github.com/saili0103/TransCLIME

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Transfer Learning in Large-scale Gaussian Graphical Models with False Discovery Rate Control

https://github.com/sdy1999/eamnet

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Edge-Aware Mirror Network for Camouflaged Object Detection

https://github.com/sunsmarterjie/SDL-Skeleton

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Adaptive Linear Span Network for Object Skeleton Detection

https://github.com/surgical-vision/colmap-match-converter

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Mismatched: Evaluating the Limits of Image Matching Approaches and Benchmarks

https://github.com/theodpzz/uav-localization

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Leveraging edge detection and neural networks for better UAV localization

https://github.com/uark-aicv/meganet

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MEGANet: Multi-Scale Edge-Guided Attention Network for Weak Boundary Polyp Segmentation

https://github.com/vectorspacelab/omnigen

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OmniGen: Unified Image Generation

https://github.com/woodfrog/floor-sp

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Floor-SP: Inverse CAD for Floorplans by Sequential Room-wise Shortest Path

https://github.com/word-ky/Edge-TOOLBOX

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Efficient Detection Framework Adaptation for Edge Computing: A Plug-and-play Neural Network Toolbox Enabling Edge Deployment

https://github.com/xavysp/DexiNed

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

https://github.com/xavysp/teed

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Tiny and Efficient Model for the Edge Detection Generalization

https://github.com/xiaofang007/cto

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Rethinking Boundary Detection in Deep Learning-Based Medical Image Segmentation

https://github.com/xiaogang00/smg-llie

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Low-Light Image Enhancement via Structure Modeling and Guidance

https://github.com/xjock/deeplebv3plus-hedplus

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DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images

https://github.com/ymgw55/scesame

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Zero-Shot Edge Detection with SCESAME: Spectral Clustering-based Ensemble for Segment Anything Model Estimation

https://github.com/yun-liu/rcf

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Richer Convolutional Features for Edge Detection

https://github.com/yunfan1202/Delving-into-Crispness

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Delving into Crispness: Guided Label Refinement for Crisp Edge Detection

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.