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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 91100 of 145 papers

TitleStatusHype
SOLOv2: Dynamic and Fast Instance SegmentationCode2
FarSee-Net: Real-Time Semantic Segmentation by Efficient Multi-scale Context Aggregation and Feature Space Super-resolution0
3D-MiniNet: Learning a 2D Representation from Point Clouds for Fast and Efficient 3D LIDAR Semantic SegmentationCode1
Real-time Fusion Network for RGB-D Semantic Segmentation Incorporating Unexpected Obstacle Detection for Road-driving ImagesCode1
Semantic Flow for Fast and Accurate Scene ParsingCode1
Using CNNs For Users Segmentation In Video See-Through Augmented Virtuality0
Efficient Video Semantic Segmentation with Labels Propagation and Refinement0
FasterSeg: Searching for Faster Real-time Semantic SegmentationCode0
LiteSeg: A Novel Lightweight ConvNet for Semantic SegmentationCode0
Real-Time Semantic Segmentation via Multiply Spatial Fusion Network0
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