搜索资源列表
Flow
- This code implements two variations of the paper \"High accuracy optic flow using a theory for warping\" presented at ECCV 2004 by Dr. Thomas Brox.
eccv 10 guided filter
- eccv2010 guide filter 论文加源代码 可以实现去雾 边缘化等操作 -eccv 2010 guide filter paper and source code
eccv06
- In this paper, a novel scale- and rotation-invariant interest point detector and descr iptor, coined SURF (Speeded Up Robust Features) is presented. It approximates or even outperforms previously proposed schemes with respect to repeatability, di
SIFTflow
- 整个场景和应用的密集通讯。 IEEE模式分析与机器智能（TPAMI），2010。 如果您使用您的研究，我们的代码，请举出我们的报纸。另外，请注意到有包ECCV版本相比略有变化。已获得密集的SIFT特征mexed。 请运行demo.h第一。如果出现错误，请去“mexDenseSIFT”和的“mexDiscreteFlow”子文件夹，并按照readme.txt文件的说明（是的，有readme.txt文件中的每个文件夹）编译cpp文件。-Dense Correspondenc
proposals
- ECCV 2010 paper "Category Independent Object Proposals"的实现。-ECCV 2010 paper "Category Independent Object Proposals" code
10.2.3
- These are one implementations of the algorithm for Face Recognition on CMU Multi-PIE. Please refer to the following paper Meng Yang, Lei Zhang, and David Zhang, "Efficient Misalignment Robust Representation Representation for Real-Tim
guided-filter-
- guided image filter 是ECCV的最佳论文并发表与PAMI上，这是其代码实现的图像增强-guided image filter is the ECCV the best paper published on PAMI, this is their code to achieve image enhancement
fast_tone_mappping
- We use the code of our fast bilateral filter to implement a tone mapping operator inspired from this SIGGRAPH 02 paper by Frédo Durand and Julie Dorsey. This code is not an exact implementation of this paper. As such, it cannot be used for comparison
Fast-Tracking
- “Fast Tracking via Dense Spatio-Temporal Context Learning,” In ECCV 2014的源代码，效果非常好。-In this paper, we present a simple yet fast and robust algorithm which exploits the spatio-temporal context for visual tracking. Our approach formulates the spatio-te
MRF1.6
- This directory contains the MRF energy minimization software accompanying the paper [1] A Comparative Study of Energy Minimization Methods for Markov Random Fields. R. Szeliski, R. Zabih, D. Scharstein, O. Veksler, V. Kolmogorov, A. Agarw
image-scaling
- 介绍了用深度学习方法做超分辨率缩放问题，都要是2014年ECCV的两篇论文-deep learning super-resolution eccv2014 paper
guided-filter-code
- 何凯文CVPR引导滤波文章对应的代码，包含增强，平滑等。带图片。-Matlab demo code for Guided Image Filtering (ECCV 2010) Contributed by Kaiming He (hkm007@ie.cuhk.edu.hk) Please note that the running time reported in the paper is C++ implementation. Usage: gu