142 papers with code • 8 benchmarks • 9 datasets Edge Detection is a fundamental image processing technique which involves computing an image gradient to quantify the magnitude and direction of edges in an
Edge detection has long been an important problem in the field of computer vision. Previous works have explored category-agnostic or category-aware edge detection. In this paper, we explore edge detection in the context of object instances. Although object boundaries could be easily derived from ...
Neuromorphic technology has recently been applied to face recognition and detection systems [4]. Spike neural networks (SNNs) and neuromorphic technology have been used to specify auto tracking capabilities combined with AI deep learning technology, 2D vs 3D facial recognition systems and industrial safe...
[1980] theory of edge detection [1983 Canny Thesis] find edge [1986 PAMI] A Computational Approach to Edge Detection [1990 PAMI] Scale-space and edge detection using anisotropic diffusion [1991 PAMI] The design and use of steerable filters [1995 PR] Multiresolution edge detection techniques [1...
1.3 Semantic edge detection (Category-Aware) 1.4 Occlusion boundary detection 1.5 Edge detection from multi-frames 2. Traditional approaches 3. Useful Links Awesome-Edge-Detection-Papers A collection of edge detection papers and corresponding source code/demo program (a.k.a. contour detection or boun...
关于模型压缩:经过了解,发现模型压缩是一个宽泛的任务概念,主要是指对于DNNs的模型的压缩优化。PapersWithCode上的专题页面为https://paperswithcode.com/task/model-compression(Benchmarks、Datasets & Codes)。本文基于Early-Exit实现的分支神经网络也属于这一大任务之下。模型压缩的次级概念整理如下: ...
ADSNet - Cross-Domain LTV Prediction with an Adaptive Siamese Network in Advertising Out of the Box Thinking - Improving Customer Lifetime Value Modelling via Expert Routing and Game Whale Detection OptDist - Learning Optimal Distribution for Customer Lifetime Value Prediction Bundle Bundle Recommendatio...
If you are using the code/data provided here in a publication, please consider citing our papers which have been included in this benchmark: @article{liu2019richer, title={Richer Convolutional Features for Edge Detection}, author={Liu, Yun and Cheng, Ming-Ming and Hu, Xiaowei and Bian, Jia...
papers for details: (1) Structured Forests for Fast Edge Detection, P. Dollár and C. Zitnick, ICCV 2013. (2) Fast Edge Detection Using Structured Forests, P. Dollár and C. Zitnick, arXiv 2014. (3) Edge Boxes: Locating Object Proposals from Edges, C. Zitnick and P. Dollár, ECCV...
In this study, we tackle the challenging fine-grained edge detection task, which refers to predicting specific edges caused by reflectance, illumination, normal, and depth changes, respectively. Prior methods exploit multi-scale convolutional networks, which are limited in three aspects: (1) Convoluti...