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Visual Object Tracking
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Visual Object Tracking is an important research topic in computer vision, image understanding and pattern recognition. Given the initial state (centre location and scale) of a target in the first frame of a video sequence, the aim of Visual Object Tracking is to automatically obtain the states of the object in the subsequent video frames.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Mamba-FETrack V2: Revisiting State Space Model for Frame-Event based Visual Object Tracking
R1-Track: Direct Application of MLLMs to Visual Object Tracking via Reinforcement Learning
Fully Spiking Neural Networks for Unified Frame-Event Object Tracking
Progressive Scaling Visual Object Tracking
Adapting SAM 2 for Visual Object Tracking: 1st Place Solution for MMVPR Challenge Multi-Modal Tracking
Towards Low-Latency Event Stream-based Visual Object Tracking: A Slow-Fast Approach
CGTrack: Cascade Gating Network with Hierarchical Feature Aggregation for UAV Tracking
Adversarial Attack for RGB-Event based Visual Object Tracking
SPMTrack: Spatio-Temporal Parameter-Efficient Fine-Tuning with Mixture of Experts for Scalable Visual Tracking
UncTrack: Reliable Visual Object Tracking with Uncertainty-Aware Prototype Memory Network
MITracker: Multi-View Integration for Visual Object Tracking
Event Stream-based Visual Object Tracking: HDETrack V2 and A High-Definition Benchmark
DeTrack: In-model Latent Denoising Learning for Visual Object Tracking
Exploring Enhanced Contextual Information for Video-Level Object Tracking
Visual Object Tracking across Diverse Data Modalities: A Review
A Distractor-Aware Memory for Visual Object Tracking with SAM2
SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory
ChatTracker: Enhancing Visual Tracking Performance via Chatting with Multimodal Large Language Model
NT-VOT211: A Large-Scale Benchmark for Night-time Visual Object Tracking
SAM2Long: Enhancing SAM 2 for Long Video Segmentation with a Training-Free Memory Tree
Improving Visual Object Tracking through Visual Prompting
General Compression Framework for Efficient Transformer Object Tracking
Enhancing Nighttime UAV Tracking with Light Distribution Suppression
Progressive Representation Learning for Real-Time UAV Tracking
Underwater Camouflaged Object Tracking Meets Vision-Language SAM2
Low-Light Object Tracking: A Benchmark
MambaEVT: Event Stream based Visual Object Tracking using State Space Model
SAM 2: Segment Anything in Images and Videos
TrackPGD: Efficient Adversarial Attack using Object Binary Masks against Robust Transformer Trackers
Robust compressive tracking via online weighted multiple instance learning
Reliable Object Tracking by Multimodal Hybrid Feature Extraction and Transformer-Based Fusion
LoReTrack: Efficient and Accurate Low-Resolution Transformer Tracking
Awesome Multi-modal Object Tracking
TENet: Targetness Entanglement Incorporating with Multi-Scale Pooling and Mutually-Guided Fusion for RGB-E Object Tracking
360VOTS: Visual Object Tracking and Segmentation in Omnidirectional Videos
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