arXiv:1805.03453
Object Tracking with Correlation Filters using Selective Single Background Patch
원문 초록
Correlation filter plays a major role in improved tracking performance compared to existing trackers. The tracker uses the adaptive correlation response to predict the location of the target. Many varieties of correlation trackers were proposed recently with high accuracy and frame rates. The paper proposes a method to select a single background patch to have a better tracking performance. The paper also contributes a variant of correlation filter by modifying the filter with image restoration filters. The approach is validated using Object Tracking Benchmark sequences.
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UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions
LD-RPS: Zero-Shot Unified Image Restoration via Latent Diffusion Recurrent Posterior Sampling
Mamba-FETrack V2: Revisiting State Space Model for Frame-Event based Visual Object Tracking
Visual and Memory Dual Adapter for Multi-Modal Object Tracking
R1-Track: Direct Application of MLLMs to Visual Object Tracking via Reinforcement Learning
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