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 quality of target and back...
上面两个流程图分别是 MDNet 以及 MDNet 的一个改进 Branchout。本文是基于 MDNet 进行改进的,主要是在速度上进行大幅度的提升,因为原始的 MDNet 采用的是 RCNN 的思路,暴力的进行特征的提取,而本文采用改进的 ROI Align 的方法进行更加高效的特征提取。此外,作者提出一种新的 loss function 使其能够取更好的区...
Code:https://github.com/bychen515/ACT 1. Background and Motivation: 本文提出一种利用 “连续” 动作空间的强化学习算法来进行跟踪。之前的 MDNET 是随机采样,然后进行打分的;而 ADNet 是 “离散”的动作选择,即:通过一系列离散的动作选择,实现 BBox 的移动,来完成跟踪。下图展示了本文方法与这两种方法的...
faster performance than the MDNet method. The search strategies of MDNet and ADNet methods are illustrated in Fig.1(a) and (b), respectively. We note that the learned iterative strategy in [10] is also far from the real-time requirement since it requires many iterative steps in every ...
【目标跟踪】Real-Time MDNet 发在ECCV2018上的一片文章,链接:Real-Time MDNet 与前作MDNet来自同一个实验室,主要工作是改进MDNet,作者说速度可以提高25倍(FPS～40)。 Motivation MDNet太慢了,FPS～1, 作者想加速它 作者认为前作在instance-level 的分类能力还是不够,想造一个分辨能力更强的模型。 这里我想解释...
MDNet: Learning Multi-Domain Convolutional Neural Networks for Visual Tracking frame, sample 4 pos (objects) and 8 neg (backgrounds), respectively. (each sequence/minibatch has 32 positive samples and 96 negative samples for training) 3. Online Tracking (1) Updating Scheme SORT 点相关的方面;...
Our tracker is about 60 times faster than the MDNet algorithm, while this deep learning method need online training and updating with high computational complexity. Therefore, the proposed tracker balances the performance and computational complexity, which is more feasible compared to other state-of-...
The development of a real-time and robust RGB-T tracker is an extremely challenging task because the tracked object may suffer from shared and specific challenges in RGB and thermal (T) modalities. In this work, we observe that the implicit attribute information can boost the model discriminabili...
(MDNET,Crest)我们的核心贡献是一种基于离线mete-learning-based的方法,用于调整在线适应跟踪中使用的初始深度网络。元学习是由深层网络的目标驱动的,深层网络可以在未来的框架中快速地适应对特定目标的鲁棒建模。理想情况下,得到的模型关注于对未来帧有用的特性,避免对背景杂波、目标的小部分或噪声的过度拟合。通过.....
Real-Time MDNet ECCV 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...