Neurocomputing, Journal Year: 2023, Volume and Issue: 569, P. 127110 - 127110
Published: Dec. 12, 2023
Language: Английский
Neurocomputing, Journal Year: 2023, Volume and Issue: 569, P. 127110 - 127110
Published: Dec. 12, 2023
Language: Английский
IET Computer Vision, Journal Year: 2023, Volume and Issue: 18(1), P. 15 - 32
Published: June 28, 2023
Abstract Conventional RGB‐T salient object detection treats RGB and thermal modalities equally to locate the common regions. However, authors observed that rich colour texture information of modality makes objects more prominent compared background; records temperature difference scene, so usually contain clear continuous edge information. In this work, a novel mirror‐complementary Transformer network (MCNet) is proposed for SOD, which supervise two separately with complementary set saliency labels under symmetrical structure. Moreover, attention‐based feature interaction serial multiscale dilated convolution (SDC)‐based fusion modules are introduced make complement adjust each other flexibly. When one fails, model can still accurately segment To demonstrate robustness challenging scenes in real world, build SOD dataset VT723 based on large public semantic segmentation used autonomous driving domain. Extensive experiments benchmark datasets show method outperforms state‐of‐the‐art approaches, including CNN‐based Transformer‐based methods. The code be found at https://github.com/jxr326/SwinMCNet .
Language: Английский
Citations
19Neurocomputing, Journal Year: 2024, Volume and Issue: 595, P. 127913 - 127913
Published: May 22, 2024
Language: Английский
Citations
9IEEE Transactions on Instrumentation and Measurement, Journal Year: 2023, Volume and Issue: 73, P. 1 - 19
Published: Dec. 1, 2023
Thermal infrared (TIR) target tracking task is not affected by illumination changes and can be tracked at night, on rainy days, foggy other extreme weather; so it widely used in auxiliary driving, unmanned aerial vehicle reconnaissance, video surveillance, scenes. However, the TIR also presents some challenges, such as intensity change, occlusion, deformation, similarity interference, on. These challenges significantly affect performance of methods. To resolve these scenarios, numerous methods have appeared recent years. The purpose this article to give a comprehensive review summary research status We first classify according their frameworks briefly summarize advantages disadvantages different methods, which better understand current progress Next, public datasets/benchmarks for testing are introduced. Subsequently, we demonstrate results several representative more intuitively show made research. Finally, discussed future direction an attempt promote development target-tracking tasks.
Language: Английский
Citations
17IEEE Transactions on Multimedia, Journal Year: 2024, Volume and Issue: 26, P. 8678 - 8690
Published: Jan. 1, 2024
RGB-Thermal pedestrian detection has shown many notable advantages in various lighting and weather conditions by combining the information from RGB-T images. Due to distinct imaging principles, modalities consist of modality-specific modality-consistent information. However, most existing methods indiscriminately integrate these two types information, which leads pollution modality To address this issue, we propose a novel mask-guided multi-level fusion network (M2FNet) for detection. M2FNet independently explores consistent specific features at three different levels, utilizing pixel-level positional masks exclusively focus on pedestrian-related features. Specifically, feature extraction level, selectively embed cross-modality differential compensation (CDC) modules design bidirectional multiscale (BMF) module fully utilize complementary enhance precision predicted masks. At global consistency mining (MGCM) is introduced capture intra-modal inter-modal pedestrians, generates highly discriminative Finally, further reduce differences, decision (MPDF) strategy dynamically weight predictions. Extensive experiments comparisons demonstrate that our proposed M2FNet, with backbones, outperforms state-of-the-art detectors both publicly available KAIST CVC-14 datasets.
Language: Английский
Citations
6Infrared Physics & Technology, Journal Year: 2023, Volume and Issue: 133, P. 104837 - 104837
Published: July 30, 2023
Language: Английский
Citations
10IEEE Signal Processing Letters, Journal Year: 2023, Volume and Issue: 30, P. 1172 - 1176
Published: Jan. 1, 2023
Multispectral
object
detection
for
autonomous
driving
is
multi-object
localization
and
classification
task
on
visible
thermal
modalities.
In
this
scenario,
modality
differences
lead
to
the
lack
of
information
in
a
single
misalignment
cross-modality
information.
To
alleviate
these
problems,
most
existing
methods
extract
based
scale
(
Language: Английский
Citations
10Neurocomputing, Journal Year: 2024, Volume and Issue: 596, P. 127959 - 127959
Published: June 4, 2024
Language: Английский
Citations
4Journal of Visual Communication and Image Representation, Journal Year: 2023, Volume and Issue: 95, P. 103882 - 103882
Published: June 22, 2023
Language: Английский
Citations
9Engineering Applications of Artificial Intelligence, Journal Year: 2025, Volume and Issue: 143, P. 110066 - 110066
Published: Jan. 16, 2025
Language: Английский
Citations
0Computers & Electrical Engineering, Journal Year: 2025, Volume and Issue: 123, P. 110234 - 110234
Published: March 14, 2025
Language: Английский
Citations
0