windowreflection Computer Vision Project

ravinder singh

Updated 2 years ago

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Classes (3)
hazed
reflection
see_through
Description

Here are a few use cases for this project:

  1. Advanced Automotive Systems: The "windowreflection" computer vision model could assist in the development of advanced autonomous driving systems. Recognizing window reflections could help autonomous cars in predicting potential hazards both in front and behind through reflections on other vehicles or buildings.

  2. Security and Surveillance: This model could be used in security camera systems to identify objects or people through window reflections, improving the overall effectiveness of surveillance.

  3. Real Estate Imagery: The model can enhance real estate photos by identifying and processing window reflections, allowing realtors to present clearer, more appealing photos of properties.

  4. Augmented Reality (AR) applications: The model could help in AR scenarios where the understanding of real-world reflections on transparent surfaces could make virtual objects interact more convincingly with the physical environment.

  5. Visual Effects and Post-Production: In the movie industry, the model can be used to enhance visual effects and post-production work by identifying and manipulating window reflections for creative purposes or to add a further level of realism.

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Cite This Project

LICENSE
CC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

                        @misc{
                            windowreflection-8ucfo_dataset,
                            title = { windowreflection Dataset },
                            type = { Open Source Dataset },
                            author = { ravinder singh },
                            howpublished = { \url{ https://universe.roboflow.com/ravinder-singh-yugpp/windowreflection-8ucfo } },
                            url = { https://universe.roboflow.com/ravinder-singh-yugpp/windowreflection-8ucfo },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { feb },
                            note = { visited on 2024-12-25 },
                            }
                        
                    

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