Giter VIP home page Giter VIP logo

Comments (3)

ligang-cs avatar ligang-cs commented on June 14, 2024

CityPersons and CrowdHuman are two popular datasets with focus on the crowd occlusion issuse. Both of them provide visible box and full-body box annotations, thus you can derive the visibility ratio by calculating the overlaps between visible and full-body boxes: visibility ratio = Area(visible) / Area(full-body). Or you mean taking visibility ratio as the regression target during the training?

from pedestriandetection-hgpd.

SamihaSara avatar SamihaSara commented on June 14, 2024

Thanks for replying. I would like to mention:

  1. Suppose I do not have the visible bounding box, then can I derive occlusion level with the full-body bounding box only?
    For example, by calculating MaxIoU ( the max IoU with other same category objects in a single image. source: https://github.com/liruilong940607/OCHumanApi)

  2. If I have a visibility score and related full body bounding box, then Can I train this model to regress the visibility score when an object is inputted? I think yes, I meant taking the visibility ratio as the regression target during the training. As my goal is to input a pedestrian's full-body bounding box and estimate its occlusion level.

from pedestriandetection-hgpd.

ligang-cs avatar ligang-cs commented on June 14, 2024

Thank you for your sharing!

  1. I don't think we can obtain the accurate occlusion ratio only with full-body boxes. I take the MaxIoU as an example. There are two overlapped persons, of which one is the occluder, and the other is the occludee. The occluder may be fully visible, but it has a high MaxIoU with the occludee. Therefore, the MaxIoU fails to indicate the occlusion ratio for occluders. Relative occlusion order is essential to accurate occlusion levels. In other words, we need to figure out which is the occluder (or occludee).
  2. Predicting the accurate visibility ratio is a difficult task. Estimating the occlusion level has been researched in previous works (Beta R-CNN, Bi-Box, MGAN), however, they usually predict the visible box or visible mask to indicate the occlusion level, instead of directly predicting a scalar (visibility ratio).

from pedestriandetection-hgpd.

Related Issues (1)

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.