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GitHub - hyseob/MDNet: Learning Multi-Domain Convolutional …
https://github.com/hyseob/MDNet
WebIntroduction. MDNet is the state-of-the-art visual tracker based on a CNN trained on a large set of tracking sequences, and the winner tracker of The VOT2015 Challenge. Detailed description of the system is provided by our paper. This software is implemented using MatConvNet and part of R-CNN.
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MDNet Demystified : Learning Multi-Domain Convolutional Neural …
https://medium.com/@r.rohit5557/mdnet-demystified-learning-multi-domain-convolutional-neural-networks-for-visual-tracking-2bb3b7948f61
WebSep 18, 2020 · Object tracking is one of the integral problems in computer vision, which involves detecting an object or multiple objects over a series of video frames. In this post, I will describe how MDNet...
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An Advanced Version of MDNet for Visual Tracking | SpringerLink
https://link.springer.com/chapter/10.1007/978-3-030-36708-4_60
WebDec 9, 2019 · MDNet [ 21] is a popular CNN-based tracking algorithm with state-of-the-art accuracy on multiple benchmarks [ 14, 28 ]. MDNet follows the tracking-by-detection framework, which samples candidate regions and classifies them with a classification CNN pre-trained on a large-scale dataset.
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GitHub - hyseob/PyMDNet: MDNet PyTorch implementation
https://github.com/hyseob/PyMDNet
WebUpdate (April, 2019) Migration to python 3.6 & pyTorch 1.0. Efficiency improvement (~5fps) ImagNet-VID pretraining. Code refactoring. Introduction. PyTorch implementation of MDNet, which runs at ~5fps with a single CPU core and a single GPU (GTX 1080 Ti). [Project] [Paper] [Matlab code] If you're using this code for your research, please cite:
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[1808.08834] Real-Time MDNet - arXiv.org
https://arxiv.org/abs/1808.08834
WebAug 27, 2018 · Ilchae Jung, Jeany Son, Mooyeol Baek, Bohyung Han. We present a fast and accurate visual tracking algorithm based on the multi-domain convolutional neural network (MDNet). The proposed approach accelerates feature extraction procedure and learns more discriminative models for instance classification; it enhances representation …
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Guided MDNet tracker with guided samples | The Visual …
https://link.springer.com/article/10.1007/s00371-021-02072-y
WebFeb 8, 2021 · Multi-domain convolutional neural network (MDNet) is a deep tracker which uses the CNN for estimating the target in each frame of the video sequence. The majority of the tracking challenges could be very easily handled by the MDNet tracker due to its offline training and online tracking features.
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Improved MDNet tracking with fast feature extraction and efficient
https://link.springer.com/article/10.1007/s11760-020-01731-2
WebJul 7, 2020 · Our algorithm, denoted by FE-MDNet, which means fast feature extraction and efficient multiple domain training for MDNet, is evaluated on OTB2015 and TrackingNet. The results show that our algorithm performs 16 times faster than MDNet with better accuracy compared to MDNet and demonstrates favorably against state-of-the-art tracking methods.
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Real-Time MDNet | Papers With Code
https://paperswithcode.com/paper/real-time-mdnet
WebWe present a fast and accurate visual tracking algorithm based on the multi-domain convolutional neural network (MDNet). The proposed approach accelerates feature extraction procedure and learns more discriminative models for instance classification; it enhances representation quality of target and background by maintaining a high …
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Real-Time MDNet - arXiv.org
https://arxiv.org/pdf/1808.08834.pdf
WebMDNet [1] is a popular CNN-based tracking algorithm with state-of-the-art accuracy. This algorithm is inspired by an object detection network, R-CNN [14]; it samples candidate regions, which are passed through a CNN pretrained on a large-scale dataset and ne-tuned at the rst frame in a test video.
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(PDF) Faster MDNet for Visual Object Tracking - ResearchGate
https://www.researchgate.net/publication/358808516_Faster_MDNet_for_Visual_Object_Tracking
WebFeb 23, 2022 · A robust tracker should perform well in three aspects: tracking accuracy, speed, and resource consumption. Considering this notion, we propose a novel model, Faster MDNet, to strike a better ...
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