Browse State-of-the-Art › RGB-T Salient Object Detection
RGB-T Salient Object Detection
6 papers with code · 0 benchmarks · 0 datasets archive 2025-07-28
RGB-T Salient Object Detection (SOD) focuses on identifying the most visually prominent objects or regions in a scene using both RGB (color) and thermal imaging data. This technique leverages the complementary strengths of visible and thermal spectrums to enhance the detection of salient objects, particularly useful in challenging visibility conditions such as night, fog, or smoke. Applications of RGB-T SOD are broad and include video/image segmentation, object recognition, visual tracking, and enhanced surveillance systems. Thermal data particularly aids in scenarios where color and texture information is insufficient for accurate detection. This method is also valuable in search and rescue operations, wildlife monitoring, and advanced driver-assistance systems (ADAS). Online benchmark and resources can be accessed at a dedicated platform for further research and development in this area.
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
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Datasets archive 2025-07-28
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Most implemented papers archive 2025-07-28
6 shown of 6 papers with code (10 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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9 Oct 2022 2 repositories listedIn addition, considering the role of thermal modality, we set up different cross-modality interaction mechanisms in the encoding phase and the decoding phase.
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19 Dec 2024 1 repository listedAlignment-free RGB-Thermal (RGB-T) salient object detection (SOD) aims to achieve robust performance in complex scenes by directly leveraging the complementary information from unaligned visible-thermal image pairs,…
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9 Jul 2024 1 repository listed Syntology ran 8 of 11 samples · 3 unverifiedHowever, in dual-modal salient object detection (SOD) model, the robustness against noisy inputs and modality missing is crucial but rarely studied.
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17 Mar 2023 1 repository listedTo further polish the expanded labels, we propose a prediction module to alleviate the sharpness of boundary.
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12 Apr 2022 1 repository listedIt is driven by Swin Transformer to extract the hierarchical features, boosted by attention mechanism to bridge the gap between two modalities, and guided by edge information to sharp the contour of salient object.
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4 Dec 2021 1 repository listed Syntology ran 3 of 3 samples · 0 unverifiedMost of the existing bi-modal (RGB-D and RGB-T) salient object detection methods utilize the convolution operation and construct complex interweave fusion structures to achieve cross-modal information integration.
Syntology lines on 2 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
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