2D Semantic Segmentation
38 papers with code • 9 benchmarks • 57 datasets
Datasets
Subtasks
Most implemented papers
xBD: A Dataset for Assessing Building Damage from Satellite Imagery
xBD is the largest building damage assessment dataset to date, containing 850, 736 building annotations across 45, 362 km\textsuperscript{2} of imagery.
Realtime Global Attention Network for Semantic Segmentation
In this paper, we proposed an end-to-end realtime global attention neural network (RGANet) for the challenging task of semantic segmentation.
Cross-task Attention Mechanism for Dense Multi-task Learning
Multi-task learning has recently become a promising solution for a comprehensive understanding of complex scenes.
SERNet-Former: Semantic Segmentation by Efficient Residual Network with Attention-Boosting Gates and Attention-Fusion Networks
AfNs are designed to improve the efficiency in the one-to-one conversion of the semantic information by deploying additional convolution layers in the decoder part.
Normalization in Training U-Net for 2D Biomedical Semantic Segmentation
In this paper, four normalization methods - BN, IN, LN and GN are compared in details, specifically for 2D biomedical semantic segmentation.
See and Think: Disentangling Semantic Scene Completion
Semantic scene completion predicts volumetric occupancy and object category of a 3D scene, which helps intelligent agents to understand and interact with the surroundings.
3D-MiniNet: Learning a 2D Representation from Point Clouds for Fast and Efficient 3D LIDAR Semantic Segmentation
Fast and efficient semantic segmentation methods are needed to match the strong computational and temporal restrictions of many of these real-world applications.
Building Disaster Damage Assessment in Satellite Imagery with Multi-Temporal Fusion
Automatic change detection and disaster damage assessment are currently procedures requiring a huge amount of labor and manual work by satellite imagery analysts.
SofGAN: A Portrait Image Generator with Dynamic Styling
To address this issue, we propose a SofGAN image generator to decouple the latent space of portraits into two subspaces: a geometry space and a texture space.
Virtual Multi-view Fusion for 3D Semantic Segmentation
Features from multiple per view predictions are finally fused on 3D mesh vertices to predict mesh semantic segmentation labels.