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Visual Tracking
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Visual Tracking is an essential and actively researched problem in the field of computer vision with various real-world applications such as robotic services, smart surveillance systems, autonomous driving, and human-computer interaction. It refers to the automatic estimation of the trajectory of an arbitrary target object, usually specified by a bounding box in the first frame, as it moves around in subsequent video frames.
Source: Learning Reinforced Attentional Representation for End-to-End Visual Tracking
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
SpatialTrackerV2: 3D Point Tracking Made Easy
CharaConsist: Fine-Grained Consistent Character Generation
MoVieS: Motion-Aware 4D Dynamic View Synthesis in One Second
What You Have is What You Track: Adaptive and Robust Multimodal Tracking
Learning to Track Any Points from Human Motion
Robotic Manipulation by Imitating Generated Videos Without Physical Demonstrations
R1-Track: Direct Application of MLLMs to Visual Object Tracking via Reinforcement Learning
Exploiting Lightweight Hierarchical ViT and Dynamic Framework for Efficient Visual Tracking
Lightweight RGB-T Tracking with Mobile Vision Transformers
Comparison of Two Methods for Stationary Incident Detection Based on Background Image
Towards Effective and Efficient Adversarial Defense with Diffusion Models for Robust Visual Tracking
TrackVLA: Embodied Visual Tracking in the Wild
CLDTracker: A Comprehensive Language Description for Visual Tracking
Hierarchical Instruction-aware Embodied Visual Tracking
VLM Can Be a Good Assistant: Enhancing Embodied Visual Tracking with Self-Improving Vision-Language Models
Efficient Motion Prompt Learning for Robust Visual Tracking
DragLoRA: Online Optimization of LoRA Adapters for Drag-based Image Editing in Diffusion Model
Towards Adaptive Meta-Gradient Adversarial Examples for Visual Tracking
DeepSORT-Driven Visual Tracking Approach for Gesture Recognition in Interactive Systems
You Are Your Best Teacher: Semi-Supervised Surgical Point Tracking with Cycle-Consistent Self-Distillation
Predicting Road Surface Anomalies by Visual Tracking of a Preceding Vehicle
TimeTracker: Event-based Continuous Point Tracking for Video Frame Interpolation with Non-linear Motion
Modality-Guided Dynamic Graph Fusion and Temporal Diffusion for Self-Supervised RGB-T Tracking
Seurat: From Moving Points to Depth
TAPIP3D: Tracking Any Point in Persistent 3D Geometry
Adversarial Attack for RGB-Event based Visual Object Tracking
St4RTrack: Simultaneous 4D Reconstruction and Tracking in the World
TAPNext: Tracking Any Point (TAP) as Next Token Prediction
POMATO: Marrying Pointmap Matching with Temporal Motion for Dynamic 3D Reconstruction
Point Tracking in Surgery--The 2024 Surgical Tattoos in Infrared (STIR) Challenge
Endo-TTAP: Robust Endoscopic Tissue Tracking via Multi-Facet Guided Attention and Hybrid Flow-point Supervision
Tracktention: Leveraging Point Tracking to Attend Videos Faster and Better
SPMTrack: Spatio-Temporal Parameter-Efficient Fine-Tuning with Mixture of Experts for Scalable Visual Tracking
Toward Scalable, Flexible Scene Flow for Point Clouds
GIFT: Generated Indoor video frames for Texture-less point tracking
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.