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Deep learning for visual tracking: A comprehensive survey
Visual target tracking is one of the most sought-after yet challenging research topics in
computer vision. Given the ill-posed nature of the problem and its popularity in a broad …
computer vision. Given the ill-posed nature of the problem and its popularity in a broad …
Satellite video single object tracking: A systematic review and an oriented object tracking benchmark
Single object tracking (SOT) in satellite video (SV) enables the continuous acquisition of
position and range information of an arbitrary object, showing promising value in remote …
position and range information of an arbitrary object, showing promising value in remote …
Autoregressive visual tracking
We present ARTrack, an autoregressive framework for visual object tracking. ARTrack
tackles tracking as a coordinate sequence interpretation task that estimates object …
tackles tracking as a coordinate sequence interpretation task that estimates object …
Mixformer: End-to-end tracking with iterative mixed attention
Tracking often uses a multi-stage pipeline of feature extraction, target information
integration, and bounding box estimation. To simplify this pipeline and unify the process of …
integration, and bounding box estimation. To simplify this pipeline and unify the process of …
Dropmae: Masked autoencoders with spatial-attention dropout for tracking tasks
In this paper, we study masked autoencoder (MAE) pretraining on videos for matching-
based downstream tasks, including visual object tracking (VOT) and video object …
based downstream tasks, including visual object tracking (VOT) and video object …
Transforming model prediction for tracking
Optimization based tracking methods have been widely successful by integrating a target
model prediction module, providing effective global reasoning by minimizing an objective …
model prediction module, providing effective global reasoning by minimizing an objective …
Robust object modeling for visual tracking
Object modeling has become a core part of recent tracking frameworks. Current popular
tackers use Transformer attention to extract the template feature separately or interactively …
tackers use Transformer attention to extract the template feature separately or interactively …
Learning spatio-temporal transformer for visual tracking
In this paper, we present a new tracking architecture with an encoder-decoder transformer
as the key component. The encoder models the global spatio-temporal feature …
as the key component. The encoder models the global spatio-temporal feature …
Transformer meets tracker: Exploiting temporal context for robust visual tracking
In video object tracking, there exist rich temporal contexts among successive frames, which
have been largely overlooked in existing trackers. In this work, we bridge the individual …
have been largely overlooked in existing trackers. In this work, we bridge the individual …
Transformer tracking with cyclic shifting window attention
Transformer architecture has been showing its great strength in visual object tracking, for its
effective attention mechanism. Existing transformer-based approaches adopt the pixel-to …
effective attention mechanism. Existing transformer-based approaches adopt the pixel-to …