Siamese neural networks: An overview
D Chicco - Artificial neural networks, 2021 - Springer
Similarity has always been a key aspect in computer science and statistics. Any time two
element vectors are compared, many different similarity approaches can be used …
element vectors are compared, many different similarity approaches can be used …
NTIRE 2024 image shadow removal challenge report
This work reviews the results of the NTIRE 2024 Challenge on Shadow Removal. Building
on the last year edition the current challenge was organized in two tracks with a track …
on the last year edition the current challenge was organized in two tracks with a track …
RFN-Nest: An end-to-end residual fusion network for infrared and visible images
In the image fusion field, the design of deep learning-based fusion methods is far from
routine. It is invariably fusion-task specific and requires a careful consideration. The most …
routine. It is invariably fusion-task specific and requires a careful consideration. The most …
Memot: Multi-object tracking with memory
We propose an online tracking algorithm that performs the object detection and data
association under a common framework, capable of linking objects after a long time span …
association under a common framework, capable of linking objects after a long time span …
SCSTCF: spatial-channel selection and temporal regularized correlation filters for visual tracking
J Zhang, W Feng, T Yuan, J Wang, AK Sangaiah - Applied Soft Computing, 2022 - Elsevier
Recently, combining multiple features into discriminative correlation filters to improve
tracking representation has shown great potential in object tracking. Existing trackers apply …
tracking representation has shown great potential in object tracking. Existing trackers apply …
Deep reinforcement learning in computer vision: a comprehensive survey
Deep reinforcement learning augments the reinforcement learning framework and utilizes
the powerful representation of deep neural networks. Recent works have demonstrated the …
the powerful representation of deep neural networks. Recent works have demonstrated the …
Siam r-cnn: Visual tracking by re-detection
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 …
The eighth visual object tracking VOT2020 challenge results
Abstract The Visual Object Tracking challenge VOT2020 is the eighth annual tracker
benchmarking activity organized by the VOT initiative. Results of 58 trackers are presented; …
benchmarking activity organized by the VOT initiative. Results of 58 trackers are presented; …
Learning discriminative model prediction for tracking
The current strive towards end-to-end trainable computer vision systems imposes major
challenges for the task of visual tracking. In contrast to most other vision problems, tracking …
challenges for the task of visual tracking. In contrast to most other vision problems, tracking …