End-to-End Object Detection with Transformers
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Updated
Jun 9, 2020 - Python
End-to-End Object Detection with Transformers
A simple demo of how to use Facebook's DETR object detector for inference. DETR: End-to-End Object Detection with Transformers.
Reproducing the Linear Multihead Attention introduced in Linformer paper (Linformer: Self-Attention with Linear Complexity)
Transformer block in tf.keras similar to PyTorch's nn.Transformer block.
TF 2.x implementation of DETR (End-to-End Object Detection with Transformers, ECCV 2020).
Fine-tune DETR object detection approach on a custom VPA Dataset.
Searching for galaxies in DSS infrared imaging using DETR
Implementation of the paper : Deformable DETR: Deformable Transformers for End-to-End Object Detection (ICLR 2021)
a simple baseline of end-to-end object detection
A Tensorflow implementation of the DETR object detection architecture.
Summary of Transformer applications for computer vision tasks.
In this work, we explain explicitly the Detection Transformer (DETR) framework for object detection & panoptic segmentation problem. Implementing the pretrained model on COCO2017 dataset and solving Wheat head detection problem.
Weapon detection using DETR model with GUI application based.
Deep learning approaches in detecting 14 different abnormalities via Chest X-Ray images
Deep learning approaches in detecting 14 different abnormalities via Chest X-Ray images
some basic transformer models about computer vision
Application for training Facebooks's pretrained Detection Transformer model on a new object detection task
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