Papers Visual Object Tracking
“Visual Object Tracking” 태그가 달린 논문 369편 · 필터 해제
DIMBA: Discretely Masked Black-Box Attack in Single Object Tracking
The adversarial attack can force a CNN-based model to produce an incorrect output by craftily manipulating human-imperceptible input. Exploring such perturbations can help us gain a deeper understanding of the vulnerabil…
Adversarial AttackMiscellaneousObject Trackingreinforcement-learning+3Towards Grand Unification of Object Tracking
We present a unified method, termed Unicorn, that can simultaneously solve four tracking problems (SOT, MOT, VOS, MOTS) with a single network using the same model parameters. Due to the fragmented definitions of the obje…
Multi-Object TrackingMulti-Object Tracking and SegmentationMultiple Object TrackingObject+3SRRT: Exploring Search Region Regulation for Visual Object Tracking
The dominant trackers generate a fixed-size rectangular region based on the previous prediction or initial bounding box as the model input, i.e., search region. While this manner obtains promising tracking efficiency, a …
Object TrackingVisual Object TrackingSiamMask: A Framework for Fast Online Object Tracking and Segmentation
In this paper we introduce SiamMask, a framework to perform both visual object tracking and video object segmentation, in real-time, with the same simple method. We improve the offline training procedure of popular fully…
Multiple Object TrackingObjectObject TrackingSegmentation+4Towards Robust Video Object Segmentation with Adaptive Object Calibration
In the booming video era, video segmentation attracts increasing research attention in the multimedia community. Semi-supervised video object segmentation (VOS) aims at segmenting objects in all target frames of a video,…
ObjectSegmentationSemantic SegmentationSemi-Supervised Video Object Segmentation+40/1 Deep Neural Networks via Block Coordinate Descent
The step function is one of the simplest and most natural activation functions for deep neural networks (DNNs). As it counts 1 for positive variables and 0 for others, its intrinsic characteristics (e.g., discontinuity a…
10-shot image generation16k2D Object Detection+92Object Tracking Using Siamese Network-Based Reinforcement Learning
Object tracking is a technique for tracking a specific object appearing in a video sequence while observing its features or changes. Recently, many algorithms showing high performance have emerged by applying the Siamese…
ObjectObject Trackingreinforcement-learningReinforcement Learning+1Revealing the Dark Secrets of Masked Image Modeling
Masked image modeling (MIM) as pre-training is shown to be effective for numerous vision downstream tasks, but how and where MIM works remain unclear. In this paper, we compare MIM with the long-dominant supervised pre-t…
Depth EstimationDiversityInductive BiasMonocular Depth Estimation+4Towards real-time and energy efficient Siamese tracking -- a hardware-software approach
Siamese trackers have been among the state-of-the-art solutions in each Visual Object Tracking (VOT) challenge over the past few years. However, with great accuracy comes great computational complexity: to achieve real-t…
Object TrackingVisual Object TrackingSiamese Object Tracking for Unmanned Aerial Vehicle: A Review and Comprehensive Analysis
Unmanned aerial vehicle (UAV)-based visual object tracking has enabled a wide range of applications and attracted increasing attention in the field of intelligent transportation systems because of its versatility and eff…
Object TrackingVisual Object TrackingCoCoLoT: Combining Complementary Trackers in Long-Term Visual Tracking
How to combine the complementary capabilities of an ensemble of different algorithms has been of central interest in visual object tracking. A significant progress on such a problem has been achieved, but considering sho…
Object TrackingVisual Object TrackingVisual TrackingTransformer Tracking with Cyclic Shifting Window Attention
Transformer architecture has been showing its great strength in visual object tracking, for its effective attention mechanism. Existing transformer-based approaches adopt the pixel-to-pixel attention strategy on flattene…
ObjectObject TrackingVisual Object TrackingA Bayesian Detect to Track System for Robust Visual Object Tracking and Semi-Supervised Model Learning
Object tracking is one of the fundamental problems in visual recognition tasks and has achieved significant improvements in recent years. The achievements often come with the price of enormous hardware consumption and ex…
Object TrackingState EstimationVariational InferenceVisual Object TrackingSingle Object Tracking Research: A Survey
Visual object tracking is an important task in computer vision, which has many real-world applications, e.g., video surveillance, visual navigation. Visual object tracking also has many challenges, e.g., object occlusion…
Objectobject-detectionObject DetectionObject Tracking+5Unsupervised Learning of Accurate Siamese Tracking
Unsupervised learning has been popular in various computer vision tasks, including visual object tracking. However, prior unsupervised tracking approaches rely heavily on spatial supervision from template-search pairs an…
Object TrackingVisual Object TrackingContext-aware Visual Tracking with Joint Meta-updating
Visual object tracking acts as a pivotal component in various emerging video applications. Despite the numerous developments in visual tracking, existing deep trackers are still likely to fail when tracking against objec…
Meta-LearningObject TrackingVisual Object TrackingVisual TrackingJoint Feature Learning and Relation Modeling for Tracking: A One-Stream Framework
The current popular two-stream, two-stage tracking framework extracts the template and the search region features separately and then performs relation modeling, thus the extracted features lack the awareness of the targ…
Object TrackingRelationVideo Object TrackingVisual Object Tracking+1MixFormer: End-to-End Tracking with Iterative Mixed Attention
Tracking often uses a multi-stage pipeline of feature extraction, target information integration, and bounding box estimation. To simplify this pipeline and unify the process of feature extraction and target information …
Semi-Supervised Video Object SegmentationVideo Object TrackingVisual Object TrackingTransforming Model Prediction for Tracking
Optimization based tracking methods have been widely successful by integrating a target model prediction module, providing effective global reasoning by minimizing an objective function. While this inductive bias integra…
Inductive BiasmodelPredictionVideo Object Tracking+1Robust Visual Tracking by Segmentation
Estimating the target extent poses a fundamental challenge in visual object tracking. Typically, trackers are box-centric and fully rely on a bounding box to define the target in the scene. In practice, objects often hav…
DecoderObject TrackingSegmentationSemantic Segmentation+5