# VLFeat Reviews
**Vendor:** VLFeat  
**Category:** [Image Recognition Software](https://www.g2.com/categories/image-recognition)  
**Average Rating:** 4.0/5.0  
**Total Reviews:** 2
## About VLFeat
VLFeat is an open source library that implements popular computer vision algorithms specializing in image understanding and local features extraction and matching, it include Fisher Vector, VLAD, SIFT, MSER, k-means, hierarchical k-means, agglomerative information bottleneck, SLIC superpixels, quick shift superpixels, large scale SVM training, and many others. It is written in C for efficiency and compatibility, with interfaces in MATLAB for ease of use, and detailed documentation throughout. It supports Windows, Mac OS X, and Linux.




## VLFeat Reviews
  ### 1. Lacks Documentation Depth

**Rating:** 3.5/5.0 stars

**Reviewed by:** Akram B. | Mid-Market (51-1000 emp.)

**Reviewed Date:** March 28, 2024

**What do you like best about VLFeat?**

Vlfeat is so cool. A computer vision researcher of the VLFeat will be a glad guy. It massively widens the choice of perfectly crafted blocks for the image recognition, like SIFT and Fisher Vectors. Here, they can be simply grabbed and built over. Thus, this open-source library saves one times and efforts of development.

**What do you dislike about VLFeat?**

The doc itself is neatly written, but the documentation is shallow at times. The multi-million dollar aircraft necessity issue gained attention when NASA’s Space Shuttle program was terminated in 2011.

**What problems is VLFeat solving and how is that benefiting you?**

It offers a good alternative for those high-cost commercial libraries and the fact is it has diverse computer vision functions to make tasks faster and easier. Therefore, I spend less time creating scripts that aren't core to my research and more time on answering my questions.

  ### 2. An extensive computer vision library

**Rating:** 4.5/5.0 stars

**Reviewed by:** Verified User in Computer Software | Mid-Market (51-1000 emp.)

**Reviewed Date:** July 23, 2018

**What do you like best about VLFeat?**

Many good baselines for popular computer vision techniques such as SIFT and HOG, along with a good SVM implementation. Also good documentation.

**What do you dislike about VLFeat?**

Doesn't support more recent deep learning techniques (but see Matconvnet). Requires Matlab to use the high level APIs (or Octave, but this is less well supported).

**Recommendations to others considering VLFeat:**

Good for baselines and reference implementations of popular computer vision methods. 

**What problems is VLFeat solving and how is that benefiting you?**

Extracting SIFT and HOG features as an object recognition baseline. Thin plate spline warps for data augmentation when training neural networks.


## VLFeat Discussions
  - [What is VLFeat used for?](https://www.g2.com/discussions/what-is-vlfeat-used-for)

- [View VLFeat pricing details and edition comparison](https://www.g2.com/products/vlfeat/reviews?section=pricing&secure%5Bexpires_at%5D=2026-05-14+23%3A25%3A53+-0500&secure%5Bsession_id%5D=464e867f-8074-448e-b62e-5c4e67ae0d8d&secure%5Btoken%5D=75703806a6ac3d748dc25a02bff0d0729ac23b75854a9b785f77fa123aca07ac&format=llm_user)

## VLFeat Features
**Recognition Type**
- Emotion Detection
- Object Detection
- Text Detection
- Motion Analysis
- Scene Reconstruction
- Logo Detection
- Explicit Content Detection
- Video Detection

**Facial Recognition**
- Facial Analysis
- Face Comparison

**Labeling**
- Model Training
- Bounding Boxes
- Custom Image Detection

**Deployment**
- Integrations

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