Implementation of the paper Recurrent Glimpse-based Decoder for Detection with Transformer.

Zhe Chen

Last update: Nov 30, 2022

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Deep Learning Deformable-DETR-REGO

Overview

REGO-Deformable DETR

By Zhe Chen, Jing Zhang, and Dacheng Tao.

This repository is the implementation of the paper Recurrent Glimpse-based Decoder for Detection with Transformer.

TODO

Release paper (finished)
Revise README
Release results
Tidy up codes
Double check and reproduce model results
Release codes

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Comments

Questions on DETR initialization

Hi! May I ask how the model is initialized for the training? Specifically, is the DETR (or equivalents like deformable DETR, etc.) part trained from scratch or initialized by the trained model?

opened by DianCh 1

Owner

Zhe Chen

GitHub

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Implementation of the paper Recurrent Glimpse-based Decoder for Detection with Transformer.

Related tags

Overview

REGO-Deformable DETR

TODO

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Comments

Questions on DETR initialization

Owner

Zhe Chen

Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-based network. Including examples for DETR, VQA.

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Official implementation for NIPS'17 paper: PredRNN: Recurrent Neural Networks for Predictive Learning Using Spatiotemporal LSTMs.

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