This competition is the final stage of the 2-day workshop on "Introduction to DL and CNN's through PyTorch" held by IECSE and Vision! By now you must've gained some interesting knowledge on CNN's and the best way to put it to use is by participating in competitions and familiarising yourself with the applications.
The most important part of any house interiors is the presence of furniture. It enhances and beautifies the house. The variety of furniture like chairs, tables, beds and their further type divisions bring out the overall grace of your house.
What does this have have do with AI? Robots are an essential part of the future. We've heard news that some robots were made/in the process of being made, to help in household works . In the recent years, a lot of models for detection and recognition of objects have been developed, commonly working with 3D information, which gives to the robots more details and accuracy. This makes it possible for the robots to identify and classify objects. With recent advancements in the field of Deep Learning based on Computer Vision, the development of Image classification models are very much necessary and are also easier to develop than before.
In this competition, we provide you with a dataset that contains various 3-D images of five types of household furniture taken in multiple angles. The dataset contains five labels:
Bed, swivel-chair, chair, sofa and table.
Objectives of this competition are:
1. Apply the knowledge and skills you've gained from this 2-day workshop to build a model.
2. To train your model using images of the given training dataset and get the highest accuracy.
3. Accurately classify a given image from testing dataset into it's respective type of furniture.
All the best folks!!