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Found 8 papers, 4 papers with code
On Advantages of Mask-level Recognition for Outlier-aware Segmentation
Most dense recognition approaches bring a separate decision in each particular pixel.
Weakly supervised training of universal visual concepts for multi-domain semantic segmentation
For instance, pickups are labeled as trucks in VIPER, cars in Vistas, and vans in ADE20k.
Panoptic SwiftNet: Pyramidal Fusion for Real-time Panoptic Segmentation
Dense panoptic prediction is a key ingredient in many existing applications such as autonomous driving, automated warehouses or remote sensing.
Multi-domain semantic segmentation with overlapping labels
Deep supervised models have an unprecedented capacity to absorb large quantities of training data.
Dense Semantic Forecasting in Video by Joint Regression of Features and Feature Motion
Feature-to-feature (F2F) module regresses the future features directly and is therefore able to account for emergent scenery.
Multimodal semantic forecasting based on conditional generation of future features
Most existing approaches address this problem as deterministic regression of future features or future predictions given observed frames.
Multi-domain semantic segmentation with pyramidal fusion
We present our submission to the semantic segmentation contest of the Robust Vision Challenge held at ECCV 2020.
Single Level Feature-to-Feature Forecasting with Deformable Convolutions
We present a method to anticipate semantic segmentation of future frames in driving scenarios based on feature-to-feature forecasting.
