What is CBNet?
CBNet is a complex architecture that forms the backbone of object detection systems. It consists of multiple backbones, including Assistant Backbones and Lead Backbone. The goal of CBNet is to extract high-level and low-level features from these backbones to effectively and accurately detect objects.
How Does CBNet Work?
CBNet is a composite architecture that takes in inputs from multiple backbones. These backbones are designed to extract different features from images at diff
The Spatial Broadcast Decoder is an architecture designed to improve the disentangling of data, reconstruction accuracy, and generalization to held-out regions in data space. It specifically benefits datasets with small objects, making it an efficient solution for various image processing tasks.
What is the Spatial Broadcast Decoder?
The Spatial Broadcast Decoder is a type of deep learning architecture that decodes encoded data into its original representation. It is different from traditiona
The topic of TNT is an innovative approach to computer vision technology that utilizes a self-attention-based neural network called Transformer to process both patch-level and pixel-level representations of images. This novel Transformer-iN-Transformer (TNT) model uses an outer transformer block to process patch embeddings and an inner transformer block to extract local features from pixel embeddings, thereby allowing for a more comprehensive view of the image features. Ultimately, the TNT model