A Strong Feature Representation for Siamese Network Tracker

2019-07-18 · Zhipeng Zhou, Rui Zhang, Dong Yin

Object tracking has important application in assistive technologies for personalized monitoring. Recent trackers choosing AlexNet as their backbone to extract features have gained great success. However, AlexNet is too shallow to form a strong feature representation, the tracker based on the Siamese network have an accuracy gap compared with state-of-the-art algorithms. To solve this problem, this paper proposes a tracker called SiamPF. Firstly, the modified pre-trained VGG16 network is fine-tuned as the backbone. Secondly, an AlexNet-like branch is added after the third convolutional layer and merged with the response map of the backbone network to form a preliminary strong feature representation. And then, a channel attention block is designed to adaptively select the contribution features. Finally, the APCE is modified to process the response map to reduce interference and focus the tracker on the target. Our SiamPF only used ILSVRC2015-VID for training, but it achieved excellent performance on OTB-2013 / OTB-2015 / VOT2015 / VOT2017, while maintaining the real-time performance of 41FPS on the GTX 1080Ti.

📄 PDF Abstract BibTeX arXiv:1907.07880

Code (0)

등록된 구현이 없습니다.

Tasks

Object Tracking

Methods 이 논문이 사용한 방법론

1x1 Convolution A 1 x 1 Convolution is a convolution with some special properties in that it can be used for dimensionality reduction,…

Convolution A convolution is a type of matrix operation, consisting of a kernel, a small matrix of weights, that slides over input data performing element-wise multiplication with the…

Siamese Network 설명 없음

Local Response Normalization Local Response Normalization is a normalization layer that implements the idea of lateral inhibition. Lateral inhibition is a concept in neurobiology that refers to the…

Grouped Convolution A Grouped Convolution uses a group of convolutions - multiple kernels per layer - resulting in multiple channel outputs per layer. This leads to wider networks helping a…

ReLU How Do I Communicate to Expedia? How Do I Communicate to Expedia? – Call ☎️ +1-(888) 829 (0881) or +1-805-330-4056 or +1-805-330-4056 for Live Support & Special Travel…

Dropout Dropout is a regularization technique for neural networks that drops a unit (along with connections) at training time with a specified probability $p$ (a common value is…

Dense Connections Dense Connections, or Fully Connected Connections, are a type of layer in a deep neural network that use a linear operation where every input is connected to every output…

MFST: Multi-Features Siamese Tracker

2021-03-01 · Zhenxi Li, Guillaume-Alexandre Bilodeau, Wassim Bouachir

Siamese trackers have recently achieved interesting results due to their balance between accuracy and speed. This success is mainly due to the fact that deep similarity networks were specifically designed to address the …

Tracking Holistic Object Representations

2019-07-21 · Axel Sauer, Elie Aljalbout, Sami Haddadin

Recent advances in visual tracking are based on siamese feature extractors and template matching. For this category of trackers, latest research focuses on better feature embeddings and similarity measures. In this work,…

Diversity Object Template Matching Visual Object Tracking+1

Multiple Convolutional Features in Siamese Networks for Object Tracking

2021-03-01 · Zhenxi Li, Guillaume-Alexandre Bilodeau, Wassim Bouachir

Siamese trackers demonstrated high performance in object tracking due to their balance between accuracy and speed. Unlike classification-based CNNs, deep similarity networks are specifically designed to address the image…

Object Object Tracking

Efficient Adversarial Attacks for Visual Object Tracking

2020-08-01 · ECCV 2020 8 · Siyuan Liang, Xingxing Wei, Siyuan Yao, Xiaochun Cao

Visual object tracking is an important task that requires the tracker to find the objects quickly and accurately. The existing state-ofthe-art object trackers, i.e., Siamese based trackers, use DNNs to attain high accura…

GPU Object Object Tracking Visual Object Tracking+1

T-SiamTPN: Temporal Siamese Transformer Pyramid Networks for Robust and Efficient UAV Tracking

2025-09-16 · Hojat Ardi, Amir Jahanshahi, Ali Diba arxiv

Aerial object tracking remains a challenging task due to scale variations, dynamic backgrounds, clutter, and frequent occlusions. While most existing trackers emphasize spatial cues, they often overlook temporal dependen…

Computational Efficiency Object Tracking