Papers Visual Object Tracking
“Visual Object Tracking” 태그가 달린 논문 369편 · 필터 해제
Pyramid Correlation based Deep Hough Voting for Visual Object Tracking
Most of the existing Siamese-based trackers treat tracking problem as a parallel task of classification and regression. However, some studies show that the sibling head structure could lead to suboptimal solutions during…
Object TrackingregressionVisual Object TrackingMulti-domain Collaborative Feature Representation for Robust Visual Object Tracking
Jointly exploiting multiple different yet complementary domain information has been proven to be an effective way to perform robust object tracking. This paper focuses on effectively representing and utilizing complement…
Object TrackingVisual Object TrackingLearning to Adversarially Blur Visual Object Tracking
Motion blur caused by the moving of the object or camera during the exposure can be a key challenge for visual object tracking, affecting tracking accuracy significantly. In this work, we explore the robustness of visual…
ObjectObject TrackingVisual Object TrackingVisual TrackingDo Different Tracking Tasks Require Different Appearance Models?
Tracking objects of interest in a video is one of the most popular and widely applicable problems in computer vision. However, with the years, a Cambrian explosion of use cases and benchmarks has fragmented the problem i…
Multi-Object TrackingMulti-Object Tracking and SegmentationMultiple People TrackingObject Tracking+10EventZoom: Learning To Denoise and Super Resolve Neuromorphic Events
We address the problem of jointly denoising and super resolving neuromorphic events, a novel visual signal that represents thresholded temporal gradients in a space-time window. The challenge for event signal process…
DenoisingImage ReconstructionObject TrackingVisual Object TrackingProgressive Unsupervised Learning for Visual Object Tracking
In this paper, we propose a progressive unsupervised learning (PUL) framework, which entirely removes the need for annotated training videos in visual tracking. Specifically, we first learn a background discriminatio…
Contrastive LearningObjectObject TrackingVisual Object Tracking+1Associating Objects with Transformers for Video Object Segmentation
This paper investigates how to realize better and more efficient embedding learning to tackle the semi-supervised video object segmentation under challenging multi-object scenarios. The state-of-the-art methods learn to …
ObjectOne-shot visual object segmentationSemantic SegmentationSemi-Supervised Video Object Segmentation+3SiamRCR: Reciprocal Classification and Regression for Visual Object Tracking
Recently, most siamese network based trackers locate targets via object classification and bounding-box regression. Generally, they select the bounding-box with maximum classification confidence as the final prediction. …
ClassificationObjectObject Trackingregression+1Contrastive Learning of Image Representations with Cross-Video Cycle-Consistency
Recent works have advanced the performance of self-supervised representation learning by a large margin. The core among these methods is intra-image invariance learning. Two different transformations of one image instanc…
Action RecognitionContrastive Learningimage-classificationImage Classification+4Two stages for visual object tracking
Siamese-based trackers have achived promising performance on visual object tracking tasks. Most existing Siamese-based trackers contain two separate branches for tracking, including classification branch and bounding box…
Image SegmentationObjectObject TrackingSegmentation+4DeepMix: Online Auto Data Augmentation for Robust Visual Object Tracking
Online updating of the object model via samples from historical frames is of great importance for accurate visual object tracking. Recent works mainly focus on constructing effective and efficient updating methods while …
Data AugmentationObjectObject TrackingVisual Object TrackingContinuity-Discrimination Convolutional Neural Network for Visual Object Tracking
This paper proposes a novel model, named Continuity-Discrimination Convolutional Neural Network (CD-CNN), for visual object tracking. Existing state-of-the-art tracking methods do not deal with temporal relationship in v…
ObjectObject TrackingVisual Object TrackingLearning Mobile CNN Feature Extraction Toward Fast Computation of Visual Object Tracking
In this paper, we construct a lightweight, high-precision and high-speed object tracking using a trained CNN. Conventional methods with trained CNNs use VGG16 network which requires powerful computational resources. Ther…
Object TrackingVisual Object TrackingTarget Transformed Regression for Accurate Tracking
Accurate tracking is still a challenging task due to appearance variations, pose and view changes, and geometric deformations of target in videos. Recent anchor-free trackers provide an efficient regression mechanism but…
regressionVisual Object TrackingVisual TrackingSTMTrack: Template-free Visual Tracking with Space-time Memory Networks
Boosting performance of the offline trained siamese trackers is getting harder nowadays since the fixed information of the template cropped from the first frame has been almost thoroughly mined, but they are poorly capab…
Video Object TrackingVisual Object TrackingVisual TrackingLearning Spatio-Temporal Transformer for Visual Tracking
In this paper, we present a new tracking architecture with an encoder-decoder transformer as the key component. The encoder models the global spatio-temporal feature dependencies between target objects and search regions…
DecoderObject TrackingVideo Object TrackingVisual Object Tracking+1Towards More Flexible and Accurate Object Tracking with Natural Language: Algorithms and Benchmark
Tracking by natural language specification is a new rising research topic that aims at locating the target object in the video sequence based on its language description. Compared with traditional bounding box (BBox) bas…
2kObjectObject TrackingSentence+2Rethinking Self-supervised Correspondence Learning: A Video Frame-level Similarity Perspective
Learning a good representation for space-time correspondence is the key for various computer vision tasks, including tracking object bounding boxes and performing video object pixel segmentation. To learn generalizable r…
Contrastive LearningObjectObject TrackingSegmentation+4Learning Target Candidate Association to Keep Track of What Not to Track
The presence of objects that are confusingly similar to the tracked target, poses a fundamental challenge in appearance-based visual tracking. Such distractor objects are easily misclassified as the target itself, leadin…
Object TrackingVideo Object TrackingVisual Object TrackingVisual TrackingTransformer Tracking
Correlation acts as a critical role in the tracking field, especially in recent popular Siamese-based trackers. The correlation operation is a simple fusion manner to consider the similarity between the template and the …
GPUObject TrackingVideo Object TrackingVisual Object Tracking+1