Papers Visual Tracking
“Visual Tracking” 태그가 달린 논문 581편 · 필터 해제
VideoTrack: Learning To Track Objects via Video Transformer
Existing Siamese tracking methods, which are built on pair-wise matching between two single frames, heavily rely on additional sophisticated mechanism to exploit temporal information among successive video frames, hi…
TripletVisual TrackingVideo Object Segmentation-aware Video Frame Interpolation
Video frame interpolation (VFI) is a very active research topic due to its broad applicability to many applications, including video enhancement, video encoding, and slow-motion effects. VFI methods have been advance…
ObjectPose EstimationSegmentationSemantic Segmentation+5Event-based Visual Tracking in Dynamic Environments
Visual object tracking under challenging conditions of motion and light can be hindered by the capabilities of conventional cameras, prone to producing images with motion blur. Event cameras are novel sensors suited to r…
Objectobject-detectionObject DetectionObject Tracking+2PVT++: A Simple End-to-End Latency-Aware Visual Tracking Framework
Visual object tracking is essential to intelligent robots. Most existing approaches have ignored the online latency that can cause severe performance degradation during real-world processing. Especially for unmanned aeri…
Object TrackingVisual Object TrackingVisual TrackingDeep Instance Segmentation and Visual Servoing to Play Jenga with a Cost-Effective Robotic System
The game of Jenga represents an inspiring benchmark for developing innovative manipulation solutions for complex tasks. Indeed, it encouraged the study of novel robotics methods to successfully extract blocks from the to…
Instance SegmentationSemantic SegmentationVisual Tracking3DMODT: Attention-Guided Affinities for Joint Detection & Tracking in 3D Point Clouds
We propose a method for joint detection and tracking of multiple objects in 3D point clouds, a task conventionally treated as a two-step process comprising object detection followed by data association. Our method embeds…
object-detectionObject DetectionVisual TrackingVisual Object Tracking in First Person Vision
The understanding of human-object interactions is fundamental in First Person Vision (FPV). Visual tracking algorithms which follow the objects manipulated by the camera wearer can provide useful information to effective…
Human-Object Interaction DetectionObjectObject TrackingVisual Object Tracking+1Tracking Small and Fast Moving Objects: A Benchmark
With more and more large-scale datasets available for training, visual tracking has made great progress in recent years. However, current research in the field mainly focuses on tracking generic objects. In this paper, w…
Visual TrackingData Fusion in Neuromarketing: Multimodal Analysis of Biosignals, Lifecycle Stages, Current Advances, Datasets, Trends, and Challenges
The primary goal of any company is to increase its profits by improving both the quality of its products and how they are advertised. In this context, neuromarketing seeks to enhance the promotion of products and generat…
Visual TrackingAVisT: A Benchmark for Visual Object Tracking in Adverse Visibility
One of the key factors behind the recent success in visual tracking is the availability of dedicated benchmarks. While being greatly benefiting to the tracking research, existing benchmarks do not pose the same difficult…
Object TrackingVisual Object TrackingVisual TrackingTransformer-based assignment decision network for multiple object tracking
Data association is a crucial component for any multiple object tracking (MOT) method that follows the tracking-by-detection paradigm. To generate complete trajectories such methods employ a data association process to e…
Multi-Object TrackingMultiple Object TrackingObject TrackingOcclusion Handling+1AiATrack: Attention in Attention for Transformer Visual Tracking
Transformer trackers have achieved impressive advancements recently, where the attention mechanism plays an important role. However, the independent correlation computation in the attention mechanism could result in nois…
Object TrackingVideo Object TrackingVisual Object TrackingVisual TrackingTowards Real-Time Visual Tracking with Graded Color-names Features
MeanShift algorithm has been widely used in tracking tasks because of its simplicity and efficiency. However, the traditional MeanShift algorithm needs to label the initial region of the target, which reduces the applica…
Real-Time Visual TrackingVisual TrackingCGMN: A Contrastive Graph Matching Network for Self-Supervised Graph Similarity Learning
Graph similarity learning refers to calculating the similarity score between two graphs, which is required in many realistic applications, such as visual tracking, graph classification, and collaborative filtering. As mo…
Collaborative FilteringGraph ClassificationGraph MatchingGraph Similarity+2Ranking-Based Siamese Visual Tracking
Current Siamese-based trackers mainly formulate the visual tracking into two independent subtasks, including classification and localization. They learn the classification subnetwork by processing each sample separately …
ClassificationVisual TrackingOnline Hybrid Lightweight Representations Learning: Its Application to Visual Tracking
This paper presents a novel hybrid representation learning framework for streaming data, where an image frame in a video is modeled by an ensemble of two distinct deep neural networks; one is a low-bit quantized network …
Representation LearningVisual TrackingBeyond Greedy Search: Tracking by Multi-Agent Reinforcement Learning-based Beam Search
To track the target in a video, current visual trackers usually adopt greedy search for target object localization in each frame, that is, the candidate region with the maximum response score will be selected as the trac…
Decision MakingImage CaptioningMulti-agent Reinforcement LearningObject Localization+3CoCoLoT: 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 TrackingSparseTT: Visual Tracking with Sparse Transformers
Transformers have been successfully applied to the visual tracking task and significantly promote tracking performance. The self-attention mechanism designed to model long-range dependencies is the key to the success of …
Visual TrackingLearning Localization-aware Target Confidence for Siamese Visual Tracking
Siamese tracking paradigm has achieved great success, providing effective appearance discrimination and size estimation by the classification and regression. While such a paradigm typically optimizes the classification a…
ClassificationregressionVisual Tracking