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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 …
Seqtrack: Sequence to sequence learning for visual object tracking
In this paper, we present a new sequence-to-sequence learning framework for visual
tracking, dubbed SeqTrack. It casts visual tracking as a sequence generation problem …
tracking, dubbed SeqTrack. It casts visual tracking as a sequence generation problem …
Cotracker: It is better to track together
We introduce CoTracker, a transformer-based model that tracks a large number of 2D points
in long video sequences. Differently from most existing approaches that track points …
in long video sequences. Differently from most existing approaches that track points …
Visual prompt multi-modal tracking
Visible-modal object tracking gives rise to a series of downstream multi-modal tracking
tributaries. To inherit the powerful representations of the foundation model, a natural modus …
tributaries. To inherit the powerful representations of the foundation model, a natural modus …
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 …
Generalized relation modeling for transformer tracking
Compared with previous two-stream trackers, the recent one-stream tracking pipeline, which
allows earlier interaction between the template and search region, has achieved a …
allows earlier interaction between the template and search region, has achieved a …
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 …
Joint feature learning and relation modeling for tracking: A one-stream framework
The current popular two-stream, two-stage tracking framework extracts the template and the
search region features separately and then performs relation modeling, thus the extracted …
search region features separately and then performs relation modeling, thus the extracted …
Aiatrack: Attention in attention for transformer visual tracking
Transformer trackers have achieved impressive advancements recently, where the attention
mechanism plays an important role. However, the independent correlation computation in …
mechanism plays an important role. However, the independent correlation computation in …