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exposure-fusion-shadow-removal
We propose a new method for effective shadow removal by regarding it as an exposure fusion problem.efficientderain
we propose EfficientDerain for high-efficiency single-image derainingmisf
DSiam
Learning Dynamic Siamese Network for Visual Object TrackingABBA
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/2107.04281jadena
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
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 Guoefficientderainplus
We further extend the efficientderain in https://github.com/tsingqguo/efficientderain via a novel predictive filtering framework.ccotssr
abcMSiam
Try to build a new tracking framework with Siamese networkfrequency-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.Love Open Source and this site? Check out how you can help us