Thermal Image Segmentation
64 papers with code • 7 benchmarks • 4 datasets
Benchmarks
These leaderboards are used to track progress in Thermal Image Segmentation
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
Libraries
Use these libraries to find Thermal Image Segmentation models and implementationsDatasets
MFNet
PST900
Most implemented papers
Depth-aware CNN for RGB-D Segmentation
laughtervv/DepthAwareCNN
•
•
ECCV 2018
Convolutional neural networks (CNN) are limited by the lack of capability to handle geometric information due to the fixed grid kernel structure.
CCNet: Criss-Cross Attention for Semantic Segmentation
speedinghzl/CCNet
•
•
ICCV 2019
Compared with the non-local block, the proposed recurrent criss-cross attention module requires 11x less GPU memory usage.
Efficient RGB-D Semantic Segmentation for Indoor Scene Analysis
TUI-NICR/ESANet
•
•
In this paper, we propose an efficient and robust RGB-D segmentation approach that can be optimized to a high degree using NVIDIA TensorRT and, thus, is well suited as a common initial processing step in a complex system for scene analysis on mobile robots.
Learning a Discriminative Feature Network for Semantic Segmentation
Most existing methods of semantic segmentation still suffer from two aspects of challenges: intra-class inconsistency and inter-class indistinction.
Specificity-preserving RGB-D Saliency Detection
To effectively fuse cross-modal features in the shared learning network, we propose a cross-enhanced integration module (CIM) and then propagate the fused feature to the next layer for integrating cross-level information.
PAIF: Perception-Aware Infrared-Visible Image Fusion for Attack-Tolerant Semantic Segmentation
liuzhu-cv/paif
•
•
We first conduct systematic analyses about the components of image fusion, investigating the correlation with segmentation robustness under adversarial perturbations.
Bi-directional Cross-Modality Feature Propagation with Separation-and-Aggregation Gate for RGB-D Semantic Segmentation
charlesCXK/RGBD_Semantic_Segmentation_PyTorch
•
•
ECCV 2020
Depth information has proven to be a useful cue in the semantic segmentation of RGB-D images for providing a geometric counterpart to the RGB representation.
Accurate RGB-D Salient Object Detection via Collaborative Learning
OIPLab-DUT/CoNet
•
•
ECCV 2020
The explicitly extracted edge information goes together with saliency to give more emphasis to the salient regions and object boundaries.
Multi-interactive Feature Learning and a Full-time Multi-modality Benchmark for Image Fusion and Segmentation
jinyuanliu-cv/segmif
•
•
ICCV 2023
Multi-modality image fusion and segmentation play a vital role in autonomous driving and robotic operation.
RTFNet: RGB-Thermal Fusion Network for Semantic Segmentation of Urban Scenes
yuxiangsun/RTFNet
•
•
IEEE ROBOTICS AND AUTOMATION LETTERS 2019
In order to enable robust and accurate semantic segmentation for autonomous vehicles, we take the advantage of thermal images and fuse both the RGB and thermal information in a novel deep neural network.
