Papers Visual Object Tracking
“Visual Object Tracking” 태그가 달린 논문 369편 · 필터 해제
Robust compressive tracking via online weighted multiple instance learning
Developing a robust object tracker is a challenging task due to factors such as occlusion, motion blur, fast motion, illumination variations, rotation, background clutter, low resolution and deformation across the frames…
Multiple Instance LearningObject TrackingVisual Object TrackingReliable Object Tracking by Multimodal Hybrid Feature Extraction and Transformer-Based Fusion
Visual object tracking, which is primarily based on visible light image sequences, encounters numerous challenges in complicated scenarios, such as low light conditions, high dynamic ranges, and background clutter. To ad…
ObjectObject TrackingVisual Object TrackingLoReTrack: Efficient and Accurate Low-Resolution Transformer Tracking
High-performance Transformer trackers have shown excellent results, yet they often bear a heavy computational load. Observing that a smaller input can immediately and conveniently reduce computations without changing the…
CPUKnowledge DistillationVisual Object TrackingAwesome Multi-modal Object Tracking
Multi-modal object tracking (MMOT) is an emerging field that combines data from various modalities, \eg vision (RGB), depth, thermal infrared, event, language and audio, to estimate the state of an arbitrary object in a …
Autonomous DrivingKnowledge DistillationMiscellaneousObject+5TENet: Targetness Entanglement Incorporating with Multi-Scale Pooling and Mutually-Guided Fusion for RGB-E Object Tracking
There is currently strong interest in improving visual object tracking by augmenting the RGB modality with the output of a visual event camera that is particularly informative about the scene motion. However, existing ap…
Object TrackingVisual Object Tracking360VOTS: Visual Object Tracking and Segmentation in Omnidirectional Videos
Visual object tracking and segmentation in omnidirectional videos are challenging due to the wide field-of-view and large spherical distortion brought by 360{\deg} images. To alleviate these problems, we introduce a nove…
ObjectObject TrackingSegmentationSemantic Segmentation+3LRR: Language-Driven Resamplable Continuous Representation against Adversarial Tracking Attacks
Visual object tracking plays a critical role in visual-based autonomous systems, as it aims to estimate the position and size of the object of interest within a live video. Despite significant progress made in this field…
ObjectObject TrackingVisual Object TrackingRTracker: Recoverable Tracking via PN Tree Structured Memory
Existing tracking methods mainly focus on learning better target representation or developing more robust prediction models to improve tracking performance. While tracking performance has significantly improved, the targ…
Visual Object TrackingVisual TrackingOmniVid: A Generative Framework for Universal Video Understanding
The core of video understanding tasks, such as recognition, captioning, and tracking, is to automatically detect objects or actions in a video and analyze their temporal evolution. Despite sharing a common goal, differen…
Action RecognitionDecoderDense Video CaptioningObject Tracking+5Exploring Dynamic Transformer for Efficient Object Tracking
The speed-precision trade-off is a critical problem for visual object tracking which usually requires low latency and deployment on constrained resources. Existing solutions for efficient tracking mainly focus on adoptin…
ObjectObject TrackingVisual Object TrackingElysium: Exploring Object-level Perception in Videos via MLLM
Multi-modal Large Language Models (MLLMs) have demonstrated their ability to perceive objects in still images, but their application in video-related tasks, such as object tracking, remains understudied. This lack of exp…
ObjectObject TrackingReferring ExpressionReferring Expression Comprehension+5SDSTrack: Self-Distillation Symmetric Adapter Learning for Multi-Modal Visual Object Tracking
Multimodal Visual Object Tracking (VOT) has recently gained significant attention due to its robustness. Early research focused on fully fine-tuning RGB-based trackers, which was inefficient and lacked generalized repres…
Object TrackingRgb-T TrackingVisual Object TrackingAutoregressive Queries for Adaptive Tracking with Spatio-TemporalTransformers
The rich spatio-temporal information is crucial to capture the complicated target appearance variations in visual tracking. However, most top-performing tracking algorithms rely on many hand-crafted components for spatio…
Visual Object TrackingVisual TrackingOneTracker: Unifying Visual Object Tracking with Foundation Models and Efficient Tuning
Visual object tracking aims to localize the target object of each frame based on its initial appearance in the first frame. Depending on the input modility, tracking tasks can be divided into RGB tracking and RGB+X (e.g.…
ObjectObject TrackingRgb-T TrackingVisual Object TrackingTracking Meets LoRA: Faster Training, Larger Model, Stronger Performance
Motivated by the Parameter-Efficient Fine-Tuning (PEFT) in large language models, we propose LoRAT, a method that unveils the power of large ViT model for tracking within laboratory-level resources. The essence of our wo…
GPUparameter-efficient fine-tuningVisual Object TrackingVisual TrackingVastTrack: Vast Category Visual Object Tracking
In this paper, we introduce a novel benchmark, dubbed VastTrack, towards facilitating the development of more general visual tracking via encompassing abundant classes and videos. VastTrack possesses several attractive p…
ObjectObject TrackingVisual Object TrackingVisual TrackingEnhancing Tracking Robustness with Auxiliary Adversarial Defense Networks
Adversarial attacks in visual object tracking have significantly degraded the performance of advanced trackers by introducing imperceptible perturbations into images. However, there is still a lack of research on designi…
Adversarial AttackAdversarial DefenseObject TrackingVisual Object TrackingACTrack: Adding Spatio-Temporal Condition for Visual Object Tracking
Efficiently modeling spatio-temporal relations of objects is a key challenge in visual object tracking (VOT). Existing methods track by appearance-based similarity or long-term relation modeling, resulting in rich tempor…
ObjectObject TrackingVisual Object TrackingReading Relevant Feature from Global Representation Memory for Visual Object Tracking
Reference features from a template or historical frames are crucial for visual object tracking. Prior works utilize all features from a fixed template or memory for visual object tracking. However, due to the dynamic nat…
Object TrackingVisual Object TrackingSpatio-temporal Prompting Network for Robust Video Feature Extraction
Frame quality deterioration is one of the main challenges in the field of video understanding. To compensate for the information loss caused by deteriorated frames, recent approaches exploit transformer-based integration…
Instance Segmentationobject-detectionObject DetectionObject Tracking+5