Papers Video Object Tracking
“Video Object Tracking” 태그가 달린 논문 107편 · 필터 해제
Fast Visual Object Tracking with Rotated Bounding Boxes
In this paper, we demonstrate a novel algorithm that uses ellipse fitting to estimate the bounding box rotation angle and size with the segmentation(mask) on the target for online and real-time visual object tracking. Ou…
GPUObjectObject TrackingVideo Object Tracking+1Learning Discriminative Model Prediction for Tracking
The current strive towards end-to-end trainable computer vision systems imposes major challenges for the task of visual tracking. In contrast to most other vision problems, tracking requires the learning of a robust targ…
modelObject TrackingPredictionVideo Object Tracking+2Unsupervised learning-based long-term superpixel tracking
Finding correspondences between structural entities decomposing images is of high interest for computer vision applications. In particular, we analyze how to accurately track superpixels - visual primitives generated by …
Object TrackingSuperpixelsVideo Object TrackingDeeper and Wider Siamese Networks for Real-Time Visual Tracking
Siamese networks have drawn great attention in visual tracking because of their balanced accuracy and speed. However, the backbone networks used in Siamese trackers are relatively shallow, such as AlexNet [18], which doe…
Real-Time Visual TrackingVideo Object TrackingVisual Object TrackingVisual TrackingFast Online Object Tracking and Segmentation: A Unifying Approach
In this paper we illustrate how to perform both visual object tracking and semi-supervised video object segmentation, in real-time, with a single simple approach. Our method, dubbed SiamMask, improves the offline trainin…
ObjectObject TrackingReal-Time Visual TrackingSegmentation+6Weakly Supervised Convolutional LSTM Approach for Tool Tracking in Laparoscopic Videos
Purpose: Real-time surgical tool tracking is a core component of the future intelligent operating room (OR), because it is highly instrumental to analyze and understand the surgical activities. Current methods for surgic…
Instrument RecognitionObject DetectionSurgical tool detectionVideo Object Tracking+1TSM: Temporal Shift Module for Efficient Video Understanding
The explosive growth in video streaming gives rise to challenges on performing video understanding at high accuracy and low computation cost. Conventional 2D CNNs are computationally cheap but cannot capture temporal rel…
3D Action RecognitionAction ClassificationAction RecognitionMicro-Action Recognition+6Deep Siamese Networks with Bayesian non-Parametrics for Video Object Tracking
We present a novel algorithm utilizing a deep Siamese neural network as a general object similarity function in combination with a Bayesian optimization (BO) framework to encode spatio-temporal information for efficient …
Bayesian OptimizationObjectObject TrackingVideo Object TrackingFully Convolutional Siamese Networks for Change Detection
This paper presents three fully convolutional neural network architectures which perform change detection using a pair of coregistered images. Most notably, we propose two Siamese extensions of fully convolutional networ…
Change DetectionChange detection for remote sensing imagesEarth ObservationVideo Object TrackingDistractor-aware Siamese Networks for Visual Object Tracking
Recently, Siamese networks have drawn great attention in visual tracking community because of their balanced accuracy and speed. However, features used in most Siamese tracking approaches can only discriminate foreground…
Incremental LearningObjectObject TrackingVideo Object Tracking+2Learning Adaptive Discriminative Correlation Filters via Temporal Consistency Preserving Spatial Feature Selection for Robust Visual Tracking
With efficient appearance learning models, Discriminative Correlation Filter (DCF) has been proven to be very successful in recent video object tracking benchmarks and competitions. However, the existing DCF paradigm suf…
Benchmarkingfeature selectionObject TrackingVideo Object Tracking+1High-speed Tracking with Multi-kernel Correlation Filters
Correlation filter (CF) based trackers are currently ranked top in terms of their performances. Nevertheless, only some of them, such as KCF~\cite{henriques15} and MKCF~\cite{tangm15}, are able to exploit the powerful di…
Video Object TrackingVocal Bursts Intensity PredictionHigh Performance Visual Tracking With Siamese Region Proposal Network
Visual object tracking has been a fundamental topic in recent years and many deep learning based trackers have achieved state-of-the-art performance on multiple benchmarks. However, most of these trackers can hardly get …
Object TrackingRegion ProposalVideo Object TrackingVisual Object Tracking+2Learning Spatial-Temporal Regularized Correlation Filters for Visual Tracking
Discriminative Correlation Filters (DCF) are efficient in visual tracking but suffer from unwanted boundary effects. Spatially Regularized DCF (SRDCF) has been suggested to resolve this issue by enforcing spatial penalty…
Video Object TrackingVisual Object TrackingVisual TrackingDepth-Adaptive Computational Policies for Efficient Visual Tracking
Current convolutional neural networks algorithms for video object tracking spend the same amount of computation for each object and video frame. However, it is harder to track an object in some frames than others, due to…
ObjectObject TrackingVideo Object TrackingVisual TrackingRobust Estimation of Similarity Transformation for Visual Object Tracking
Most of existing correlation filter-based tracking approaches only estimate simple axis-aligned bounding boxes, and very few of them is capable of recovering the underlying similarity transformation. To tackle this chall…
ObjectObject TrackingVideo Object TrackingVisual Object TrackingMAVOT: Memory-Augmented Video Object Tracking
We introduce a one-shot learning approach for video object tracking. The proposed algorithm requires seeing the object to be tracked only once, and employs an external memory to store and remember the evolving features o…
ObjectObject TrackingOne-Shot LearningVideo Object Tracking+1Context-Aware Correlation Filter Tracking
Correlation filter (CF) based trackers have recently gained a lot of popularity due to their impressive performance on benchmark datasets, while maintaining high frame rates. A significant amount of recent research focus…
Video Object TrackingQuo Vadis, Action Recognition? A New Model and the Kinetics Dataset
The paucity of videos in current action classification datasets (UCF-101 and HMDB-51) has made it difficult to identify good video architectures, as most methods obtain similar performance on existing small-scale benchma…
Action ClassificationAction RecognitionGeneral Classificationimage-classification+2Learning Background-Aware Correlation Filters for Visual Tracking
Correlation Filters (CFs) have recently demonstrated excellent performance in terms of rapidly tracking objects under challenging photometric and geometric variations. The strength of the approach comes from its ability …
ObjectVideo Object TrackingVisual Tracking