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Real-Time Semantic Segmentation

Semantic Segmentation is a computer vision task that involves assigning a semantic label to each pixel in an image. In Real-Time Semantic Segmentation, the goal is to perform this labeling quickly and accurately in real-time, allowing for the segmentation results to be used for tasks such as object recognition, scene understanding, and autonomous navigation.

( Image credit: TorchSeg )

Papers

Showing 1120 of 145 papers

TitleStatusHype
BiSeNet: Bilateral Segmentation Network for Real-time Semantic SegmentationCode1
Bilateral Network with Residual U-blocks and Dual-Guided Attention for Real-time Semantic SegmentationCode1
Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road ScenesCode1
HarDNet: A Low Memory Traffic NetworkCode1
Real-time Semantic Segmentation via Spatial-detail Guided Context PropagationCode1
ENet: A Deep Neural Network Architecture for Real-Time Semantic SegmentationCode1
FBSNet: A Fast Bilateral Symmetrical Network for Real-Time Semantic SegmentationCode1
CFPNet: Channel-wise Feature Pyramid for Real-Time Semantic SegmentationCode1
3D-MiniNet: Learning a 2D Representation from Point Clouds for Fast and Efficient 3D LIDAR Semantic SegmentationCode1
AsymFormer: Asymmetrical Cross-Modal Representation Learning for Mobile Platform Real-Time RGB-D Semantic SegmentationCode1
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