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Found 5 papers, 1 papers with code
TSGB: Target-Selective Gradient Backprop for Probing CNN Visual Saliency
Inspired by those observations, we propose a novel visual saliency method, termed Target-Selective Gradient Backprop (TSGB), which leverages rectification operations to effectively emphasize target classes and further efficiently propagate the saliency to the image space, thereby generating target-selective and fine-grained saliency maps.
Robust Visual Tracking via Statistical Positive Sample Generation and Gradient Aware Learning
In this paper, we propose a robust tracking method via Statistical Positive sample generation and Gradient Aware learning (SPGA) to address the above two limitations.
Correlation filter tracking with adaptive proposal selection for accurate scale estimation
In this paper, we propose an adaptive proposal selection algorithm which can generate a small number of high-quality proposals to handle the problem of scale variations for visual object tracking.
Asynchronous Tracking-by-Detection on Adaptive Time Surfaces for Event-based Object Tracking
To achieve this goal, we present an Adaptive Time-Surface with Linear Time Decay (ATSLTD) event-to-frame conversion algorithm, which asynchronously and effectively warps the spatio-temporal information of asynchronous retinal events to a sequence of ATSLTD frames with clear object contours.
DSNet: Deep and Shallow Feature Learning for Efficient Visual Tracking
In recent years, Discriminative Correlation Filter (DCF) based tracking methods have achieved great success in visual tracking.
