Papers Visual Object Tracking
“Visual Object Tracking” 태그가 달린 논문 369편 · 필터 해제
Event Stream-based Visual Object Tracking: HDETrack V2 and A High-Definition Benchmark
We then introduce a novel hierarchical knowledge distillation strategy that incorporates the similarity matrix, feature representation, and response map-based distillation to guide the learning of the student Transformer…
Knowledge DistillationObject TrackingVisual Object TrackingDeTrack: In-model Latent Denoising Learning for Visual Object Tracking
Previous visual object tracking methods employ image-feature regression models or coordinate autoregression models for bounding box prediction. Image-feature regression methods heavily depend on matching results and do n…
DenoisingObject TrackingVisual Object TrackingAutoregressive Sequential Pretraining for Visual Tracking
Recent advancements in visual object tracking have shifted towards a sequential generation paradigm, where object deformation and motion exhibit strong temporal dependencies. Despite the importance of these dependenc…
ObjectObject TrackingVisual Object TrackingVisual TrackingDreamTrack: Dreaming the Future for Multimodal Visual Object Tracking
Aiming to achieve class-agnostic perception in visual object tracking, current trackers commonly formulate tracking as a one-shot detection problem with the template-matching architecture. Despite the success, severe…
Object TrackingTemplate MatchingVisual Object TrackingVisual TrackingExploring Enhanced Contextual Information for Video-Level Object Tracking
Contextual information at the video level has become increasingly crucial for visual object tracking. However, existing methods typically use only a few tokens to convey this information, which can lead to information lo…
ObjectObject TrackingSemi-Supervised Video Object SegmentationVideo Object Tracking+2Visual Object Tracking across Diverse Data Modalities: A Review
Visual Object Tracking (VOT) is an attractive and significant research area in computer vision, which aims to recognize and track specific targets in video sequences where the target objects are arbitrary and class-agnos…
Object TrackingVisual Object TrackingA Distractor-Aware Memory for Visual Object Tracking with SAM2
Memory-based trackers are video object segmentation methods that form the target model by concatenating recently tracked frames into a memory buffer and localize the target by attending the current image to the buffered …
Object TrackingSemi-Supervised Video Object SegmentationVisual Object TrackingVisual TrackingSAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory
The Segment Anything Model 2 (SAM 2) has demonstrated strong performance in object segmentation tasks but faces challenges in visual object tracking, particularly when managing crowded scenes with fast-moving or self-occ…
Object TrackingVisual Object TrackingVisual TrackingChatTracker: Enhancing Visual Tracking Performance via Chatting with Multimodal Large Language Model
Visual object tracking aims to locate a targeted object in a video sequence based on an initial bounding box. Recently, Vision-Language~(VL) trackers have proposed to utilize additional natural language descriptions to e…
Language ModelingLanguage ModellingLarge Language ModelMultimodal Large Language Model+4NT-VOT211: A Large-Scale Benchmark for Night-time Visual Object Tracking
Many current visual object tracking benchmarks such as OTB100, NfS, UAV123, LaSOT, and GOT-10K, predominantly contain day-time scenarios while the challenges posed by the night-time has been less investigated. It is prim…
Object TrackingVideo Object TrackingVisual Object TrackingSAM2Long: Enhancing SAM 2 for Long Video Segmentation with a Training-Free Memory Tree
The Segment Anything Model 2 (SAM 2) has emerged as a powerful foundation model for object segmentation in both images and videos, paving the way for various downstream video applications. The crucial design of SAM 2 for…
Heuristic SearchObjectSegmentationSemantic Segmentation+4Improving Visual Object Tracking through Visual Prompting
Learning a discriminative model to distinguish a target from its surrounding distractors is essential to generic visual object tracking. Dynamic target representation adaptation against distractors is challenging due to …
ObjectObject TrackingVisual Object Tracking+2General Compression Framework for Efficient Transformer Object Tracking
Transformer-based trackers have established a dominant role in the field of visual object tracking. While these trackers exhibit promising performance, their deployment on resource-constrained devices remains challenging…
Model CompressionObjectObject TrackingVisual Object TrackingUnderwater Camouflaged Object Tracking Meets Vision-Language SAM2
Over the past decade, significant progress has been made in visual object tracking, largely due to the availability of large-scale datasets. However, these datasets have primarily focused on open-air scenarios and have l…
ObjectObject TrackingVideo SegmentationVideo Semantic Segmentation+1Progressive Representation Learning for Real-Time UAV Tracking
Visual object tracking has significantly promoted autonomous applications for unmanned aerial vehicles (UAVs). However, learning robust object representations for UAV tracking is especially challenging in complex dynamic…
ObjectObject TrackingRepresentation LearningVisual Object TrackingEnhancing Nighttime UAV Tracking with Light Distribution Suppression
Visual object tracking has boosted extensive intelligent applications for unmanned aerial vehicles (UAVs). However, the state-of-the-art (SOTA) enhancers for nighttime UAV tracking always neglect the uneven light distrib…
Object Trackingparameter estimationVisual Object TrackingLow-Light Object Tracking: A Benchmark
In recent years, the field of visual tracking has made significant progress with the application of large-scale training datasets. These datasets have supported the development of sophisticated algorithms, enhancing the …
ObjectObject TrackingVisual Object TrackingVisual TrackingMambaEVT: Event Stream based Visual Object Tracking using State Space Model
Event camera-based visual tracking has drawn more and more attention in recent years due to the unique imaging principle and advantages of low energy consumption, high dynamic range, and dense temporal resolution. Curren…
MambaObject LocalizationObject TrackingVisual Object Tracking+1SAM 2: Segment Anything in Images and Videos
We present Segment Anything Model 2 (SAM 2), a foundation model towards solving promptable visual segmentation in images and videos. We build a data engine, which improves model and data via user interaction, to collect …
Image SegmentationRobot Manipulation GeneralizationSegmentationSemantic Segmentation+5TrackPGD: Efficient Adversarial Attack using Object Binary Masks against Robust Transformer Trackers
Adversarial perturbations can deceive neural networks by adding small, imperceptible noise to the input. Recent object trackers with transformer backbones have shown strong performance on tracking datasets, but their adv…
Adversarial AttackAdversarial RobustnessObjectObject Tracking+1