CURE-OR: Challenging Unreal and Real Environments for Object Recognition
We introduced an image dataset denoted as Challenging Unreal and Real Environments for Object Recognition (CURE-OR-1M), whose characteristics are summarized below. In CURE-OR-1M dataset, there are 1,000,000 images of 100 objects with varying size, color, and texture, captured with multiple devices in different setups. In contrast to existing studies, the majority of images in the CURE-OR-1M dataset were acquired with smartphones and tested with off-the-shelf applications, because we want to benchmark the recognition performance of devices and applications that are used in our daily lives rather than testing algorithms that can only work with specific hardware or testing devices that we rarely utilize.
|Object Classes (number of objects/class)||Number of images per object||Controlled condition (level)||Background||Acquisition|
|toy (23) personal (10) office (14) household (27) sports/ent. (10) health (16)||10,000||Perspective (5) background (5) challenge (78)||white 2D textured 2D (2) real 3D (2)||DSLR webcam smartphones|
Will be available soon, please stay tuned!