tsingqguo/MSiam

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1
Language
MATLAB
License
MIT License
Created about 6 years ago
Updated about 6 years ago

tsingqguo/MSiam

tsingqguo

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Try to build a new tracking framework with Siamese network

exposure-fusion-shadow-removal

We propose a new method for effective shadow removal by regarding it as an exposure fusion problem.

Jupyter Notebook

efficientderain

we propose EfficientDerain for high-efficiency single-image deraining

misf

DSiam

Learning Dynamic Siamese Network for Visual Object Tracking

ABBA

inpaint4shadow

We propose the shadow-guided inpainting task to take advantage of the shadow removal and image inpainting.

bgmix

We propose a novel data augmentation by enriching the backgrounds for change detection in a weakly-superivsed way.

AttackTracker

jpgnet

We proposed a novel framework for image inpainting. https://arxiv.org/abs/2107.04281

jadena

Official implementation of "Can You Spot the Chameleon? Adversarially Camouflaging Images from Co-Salient Object Detection" in CVPR 2022.

ABA

We propose the adversarial blur attack (ABA) against visual object tracking.

robustOT

We build a benchmark to involve existing adversairal tracking attacks and defense methods and evaluates their performance, which could trick a series of novel works and push the progress to build a robust tracking system.

deeprhythm

irad

We introduce a novel approach to counter adversarial attacks, namely, image resampling. The underlying rationale behind our idea is that image resampling can alleviate the influence of adversarial perturbations while preserving essential semantic information, thereby conferring an inherent advantage in defending against adversarial attacks.

sharel

We propose a shadow-removal benchmark dataset (i.e., SHAREL) to explore the mutual influence of shadow removal and facial landmark detection tasks.

tsingqguo.github.io

Homepage of Qing Guo

efficientderainplus

We further extend the efficientderain in https://github.com/tsingqguo/efficientderain via a novel predictive filtering framework.

ccotssr

frequency-tuned-ACM

This repository contains the demos of frequency-tuned ACM.

evadingfakedetector

We propose a statistical consistency attack (StatAttack) against diverse DeepFake detectors.

resample4defense

We have identified a novel adversarial defense solution, i.e., image resampling, which can break the adversarial textures while maintaining the main semantic information in the input image. This work has been accepted to ICLR 2024.