Thermal Image Segmentation
64 papers with code • 7 benchmarks • 4 datasets
Benchmarks
These leaderboards are used to track progress in Thermal Image Segmentation
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Libraries
Use these libraries to find Thermal Image Segmentation models and implementationsDatasets
MFNet
PST900
Most implemented papers
BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation
PaddlePaddle/PaddleSeg
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ECCV 2018
Semantic segmentation requires both rich spatial information and sizeable receptive field.
ICNet for Real-Time Semantic Segmentation on High-Resolution Images
We focus on the challenging task of real-time semantic segmentation in this paper.
LinkNet: Exploiting Encoder Representations for Efficient Semantic Segmentation
qubvel/segmentation_models
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As a result they are huge in terms of parameters and number of operations; hence slow too.
ERFNet: Efficient Residual Factorized ConvNet for Real-time Semantic Segmentation
osmr/imgclsmob
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Transactions on Intelligent Transportation Systems (T-ITS) 2017
A comprehensive set of experiments on the publicly available Cityscapes dataset demonstrates that our system achieves an accuracy that is similar to the state of the art, while being orders of magnitude faster to compute than other architectures that achieve top precision.
Context Encoding for Semantic Segmentation
zhanghang1989/PyTorch-Encoding
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CVPR 2018
In this paper, we explore the impact of global contextual information in semantic segmentation by introducing the Context Encoding Module, which captures the semantic context of scenes and selectively highlights class-dependent featuremaps.
Dual Attention Network for Scene Segmentation
Specifically, we append two types of attention modules on top of traditional dilated FCN, which model the semantic interdependencies in spatial and channel dimensions respectively.
Panoptic Feature Pyramid Networks
facebookresearch/detectron2
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CVPR 2019
In this work, we perform a detailed study of this minimally extended version of Mask R-CNN with FPN, which we refer to as Panoptic FPN, and show it is a robust and accurate baseline for both tasks.
Segmenter: Transformer for Semantic Segmentation
rstrudel/segmenter
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ICCV 2021
In this paper we introduce Segmenter, a transformer model for semantic segmentation.
Understanding Convolution for Semantic Segmentation
This framework 1) effectively enlarges the receptive fields (RF) of the network to aggregate global information; 2) alleviates what we call the "gridding issue" caused by the standard dilated convolution operation.
Full-Resolution Residual Networks for Semantic Segmentation in Street Scenes
Therefore, additional processing steps have to be performed in order to obtain pixel-accurate segmentation masks at the full image resolution.
