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Deep learning for visual tracking: A comprehensive survey
SM Marvasti-Zadeh, L Cheng… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
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 …
Emergent correspondence from image diffusion
Finding correspondences between images is a fundamental problem in computer vision. In
this paper, we show that correspondence emerges in image diffusion models without any …
this paper, we show that correspondence emerges in image diffusion models without any …
Towards grand unification of object tracking
We present a unified method, termed Unicorn, that can simultaneously solve four tracking
problems (SOT, MOT, VOS, MOTS) with a single network using the same model parameters …
problems (SOT, MOT, VOS, MOTS) with a single network using the same model parameters …
Learning target candidate association to keep track of what not to track
C Mayer, M Danelljan, DP Paudel… - Proceedings of the …, 2021 - openaccess.thecvf.com
The presence of objects that are confusingly similar to the tracked target, poses a
fundamental challenge in appearance-based visual tracking. Such distractor objects are …
fundamental challenge in appearance-based visual tracking. Such distractor objects are …
Particle video revisited: Tracking through occlusions using point trajectories
AW Harley, Z Fang, K Fragkiadaki - European Conference on Computer …, 2022 - Springer
Tracking pixels in videos is typically studied as an optical flow estimation problem, where
every pixel is described with a displacement vector that locates it in the next frame. Even …
every pixel is described with a displacement vector that locates it in the next frame. Even …
Siam r-cnn: Visual tracking by re-detection
P Voigtlaender, J Luiten, PHS Torr… - Proceedings of the …, 2020 - openaccess.thecvf.com
Abstract We present Siam R-CNN, a Siamese re-detection architecture which unleashes the
full power of two-stage object detection approaches for visual object tracking. We combine …
full power of two-stage object detection approaches for visual object tracking. We combine …
Fast online object tracking and segmentation: A unifying approach
Q Wang, L Zhang, L Bertinetto… - Proceedings of the …, 2019 - openaccess.thecvf.com
In this paper we illustrate how to perform both visual object tracking and semi-supervised
video object segmentation, in real-time, with a single simple approach. Our method, dubbed …
video object segmentation, in real-time, with a single simple approach. Our method, dubbed …
A survey on deep learning technique for video segmentation
T Zhou, F Porikli, DJ Crandall… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
Video segmentation—partitioning video frames into multiple segments or objects—plays a
critical role in a broad range of practical applications, from enhancing visual effects in movie …
critical role in a broad range of practical applications, from enhancing visual effects in movie …
Got-10k: A large high-diversity benchmark for generic object tracking in the wild
We introduce here a large tracking database that offers an unprecedentedly wide coverage
of common moving objects in the wild, called GOT-10k. Specifically, GOT-10k is built upon …
of common moving objects in the wild, called GOT-10k. Specifically, GOT-10k is built upon …
Lasot: A high-quality benchmark for large-scale single object tracking
In this paper, we present LaSOT, a high-quality benchmark for Large-scale Single Object
Tracking. LaSOT consists of 1,400 sequences with more than 3.5 M frames in total. Each …
Tracking. LaSOT consists of 1,400 sequences with more than 3.5 M frames in total. Each …