DETRlike
DETRlike is a term used to describe models that share similarities with the DETR (DEtection TRansformer) architecture, which was introduced by Facebook AI in 2020. DETR is a novel approach to object detection that leverages the transformer architecture, a type of neural network that has shown great success in natural language processing tasks. Unlike traditional object detection methods that rely on convolutional neural networks (CNNs) and anchor-based approaches, DETR uses a transformer encoder-decoder architecture to directly predict object bounding boxes and class labels in a single pass.
The key innovation of DETR is its use of a set prediction loss, which allows it to
DETRlike models build upon the DETR architecture by incorporating modifications or enhancements to address specific challenges
Overall, DETRlike models represent an exciting direction in object detection research, offering a promising alternative to