Papers Visual Tracking
“Visual Tracking” 태그가 달린 논문 581편 · 필터 해제
Object Tracking via Dynamic Feature Selection Processes
DFST proposes an optimized visual tracking algorithm based on the real-time selection of locally and temporally discriminative features. A feature selection mechanism is embedded in the Adaptive colour Names (CN) trackin…
feature selectionObjectObject TrackingPosition+1Real-Time Visual Tracking: Promoting the Robustness of Correlation Filter Learning
Correlation filtering based tracking model has received lots of attention and achieved great success in real-time tracking, however, the lost function in current correlation filtering paradigm could not reliably response…
Real-Time Visual TrackingVisual TrackingModeling and Propagating CNNs in a Tree Structure for Visual Tracking
We present an online visual tracking algorithm by managing multiple target appearance models in a tree structure. The proposed algorithm employs Convolutional Neural Networks (CNNs) to represent target appearances, where…
Object TrackingVisual Object TrackingVisual TrackingFundamental principles of cortical computation: unsupervised learning with prediction, compression and feedback
There has been great progress in understanding of anatomical and functional microcircuitry of the primate cortex. However, the fundamental principles of cortical computation - the principles that allow the visual cortex …
Visual TrackingLearning Spatially Regularized Correlation Filters for Visual Tracking
Robust and accurate visual tracking is one of the most challenging computer vision problems. Due to the inherent lack of training data, a robust approach for constructing a target appearance model is crucial. Recently, d…
Video Object TrackingVisual TrackingBeyond Correlation Filters: Learning Continuous Convolution Operators for Visual Tracking
Discriminative Correlation Filters (DCF) have demonstrated excellent performance for visual object tracking. The key to their success is the ability to efficiently exploit available negative data by including all shifted…
Object TrackingPoint TrackingVisual Object TrackingVisual TrackingSparse vs. Non-sparse: Which One Is Better for Practical Visual Tracking?
Recently, sparse representation based visual tracking methods have attracted increasing attention in the computer vision community. Although achieve superior performance to traditional tracking methods, however, a basic …
Visual TrackingVisual Tracking via Shallow and Deep Collaborative Model
In this paper, we propose a robust tracking method based on the collaboration of a generative model and a discriminative classifier, where features are learned by shallow and deep architectures, respectively. For the gen…
Incremental LearningmodelVisual TrackingUnsupervised Learning from Continuous Video in a Scalable Predictive Recurrent Network
Understanding visual reality involves acquiring common-sense knowledge about countless regularities in the visual world, e.g., how illumination alters the appearance of objects in a scene, and how motion changes their ap…
Common Sense ReasoningVisual TrackingAction Recognition with Joint Attention on Multi-Level Deep Features
We propose a novel deep supervised neural network for the task of action recognition in videos, which implicitly takes advantage of visual tracking and shares the robustness of both deep Convolutional Neural Network (CNN…
Action RecognitionAction Recognition In VideosTemporal Action LocalizationVisual TrackingReconNet: Non-Iterative Reconstruction of Images From Compressively Sensed Measurements
The goal of this paper is to present a non-iterative and more importantly an extremely fast algorithm to reconstruct images from compressively sensed (CS) random measurements. To this end, we propose a novel convolution…
Real-Time Visual TrackingVisual TrackingSTCT: Sequentially Training Convolutional Networks for Visual Tracking
Due to the limited amount of training samples, fine-tuning pre-trained deep models online is prone to over-fitting. In this paper, we propose a sequential training method for convolutional neural networks (CNNs) to effec…
Visual TrackingRecurrently Target-Attending Tracking
Robust visual tracking is a challenging task in computer vision. Due to the accumulation and propagation of estimation error, model drifting often occurs and degrades the tracking performance. To mitigate this problem, i…
Visual TrackingIn Defense of Sparse Tracking: Circulant Sparse Tracker
Sparse representation has been introduced to visual tracking by finding the best target candidate with minimal reconstruction error within the particle filter framework. However, most sparse representation based trackers…
Visual TrackingHedged Deep Tracking
In recent years, several methods have been developed to utilize hierarchical features learned from a deep convolutional neural network (CNN) for visual tracking. However, as the features from a certain CNN layer characte…
Visual TrackingStructural Correlation Filter for Robust Visual Tracking
In this paper, we propose a novel structural correlation filter (SCF) model for robust visual tracking. The proposed SCF model takes part-based tracking strategies into account in a correlation filter tracker, and exploi…
Computational EfficiencyVisual TrackingVisual Tracking Using Attention-Modulated Disintegration and Integration
In this paper, we present a novel attention-modulated visual tracking algorithm that decomposes an object into multiple cognitive units, and trains multiple elementary trackers in order to modulate the distribution of at…
ObjectVisual TrackingSparse Coding and Counting for Robust Visual Tracking
In this paper, we propose a novel sparse coding and counting method under Bayesian framwork for visual tracking. In contrast to existing methods, the proposed method employs the combination of L0 and L1 norm to regulariz…
Visual TrackingDeformable Parts Correlation Filters for Robust Visual Tracking
Deformable parts models show a great potential in tracking by principally addressing non-rigid object deformations and self occlusions, but according to recent benchmarks, they often lag behind the holistic approaches. T…
ObjectObject LocalizationVisual TrackingEnforcing Template Representability and Temporal Consistency for Adaptive Sparse Tracking
Sparse representation has been widely studied in visual tracking, which has shown promising tracking performance. Despite a lot of progress, the visual tracking problem is still a challenging task due to appearance varia…
DescriptiveVisual Tracking