Decompose to Adapt: Cross-domain Object Detection via Feature Disentanglement

Last update: Nov 24, 2022

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Overview

Decompose to Adapt: Cross-domain Object Detection via Feature Disentanglement

In this project, we proposed a Domain Disentanglement Faster-RCNN (DDF) for cross-domain object detection, from the view of feature disentanglement.

The implementations are for our paper published in IEEE Transactions on Multimedia:

Decompose to Adapt: Cross-domain Object Detection via Feature Disentanglement

**The overall code will be released later on.

Visual Examples of the features

Our proposed framework: Domain Disentanglement Faster-RCNN (DDF)

Contact

Please contact Dongnan Liu ([email protected]) regarding any issues.

License

DDF is released under the MIT license. See LICENSE for additional details.

Owner

Dongnan Liu @ USYD [email protected]

GitHub Repository

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Decompose to Adapt: Cross-domain Object Detection via Feature Disentanglement

Related tags

Overview

Decompose to Adapt: Cross-domain Object Detection via Feature Disentanglement

Visual Examples of the features

Our proposed framework: Domain Disentanglement Faster-RCNN (DDF)

Contact

License

Owner

Creating a Linear Program Solver by Implementing the Simplex Method in Python with NumPy

MOpt-AFL provided by the paper "MOPT: Optimized Mutation Scheduling for Fuzzers"

PyTorch code for 'Efficient Single Image Super-Resolution Using Dual Path Connections with Multiple Scale Learning'

An implementation of the AlphaZero algorithm for Gomoku (also called Gobang or Five in a Row)

Face Synthetics dataset is a collection of diverse synthetic face images with ground truth labels.

Synthetic Scene Text from 3D Engines

Object DGCNN and DETR3D, Our implementations are built on top of MMdetection3D.

Source codes for the paper "Local Additivity Based Data Augmentation for Semi-supervised NER"

This's an implementation of deepmind Visual Interaction Networks paper using pytorch

PyMove is a Python library to simplify queries and visualization of trajectories and other spatial-temporal data

classify fashion-mnist dataset with pytorch

Rethinking Portrait Matting with Privacy Preserving

Bag of Tricks for Natural Policy Gradient Reinforcement Learning

Tutorial repo for an end-to-end Data Science project

ChainerRL is a deep reinforcement learning library built on top of Chainer.

Code for "Learning From Multiple Experts: Self-paced Knowledge Distillation for Long-tailed Classification", ECCV 2020 Spotlight

Regularized Frank-Wolfe for Dense CRFs: Generalizing Mean Field and Beyond

Predictive Maintenance LSTM

Python scripts for performing object detection with the 1000 labels of the ImageNet dataset in ONNX.

FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.