Real-Time Semantic Segmentation
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Benchmarks
Cityscapes test
CamVid
Cityscapes val
NYU Depth v2
COCO-Stuff
Cityscapes
FLAME
HelixNet
Most implemented
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
Pyramid Scene Parsing Network
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation
Fully Convolutional Networks for Semantic Segmentation
HarDNet: A Low Memory Traffic Network
Fast-SCNN: Fast Semantic Segmentation Network
Papers
EGRNet: A Lightweight Semantic Segmentation Network with Edge-Gated Refinement and Adversarial Sensing
As autonomous systems and smart cities continue to evolve, the demand for efficient and robust scene understanding becomes increasingly critical. Semantic segmentation plays a key role in enabling autonomous vehicles to …
Real-Time Semantic SegmentationScene UnderstandingAutonomous VehiclesAdversarial AttackPILOT: A Data-Free Continual Learning Approach for Real-Time Semantic Segmentation via Boundary Guidance
Real-time semantic segmentation models offer an excellent balance between accuracy and inference speed. However, deploying these models in dynamic real world environments often requires the ability to learn novel classes…
Real-Time Semantic SegmentationIncremental LearningContinual LearningSkySeg: Collaborative Onboard Semantic Segmentation with Heterogeneous UAVs in the Wild
The demand for unmanned aerial vehicle (UAV)-based image acquisition and analysis has surged, with UAVs increasingly utilized for semantic segmentation tasks. To meet the real-time analysis requirements of UAV remote sen…
Real-Time Semantic SegmentationTest-time AdaptationSemantic-Fast-SAM: Efficient Semantic Segmenter
We propose Semantic-Fast-SAM (SFS), a semantic segmentation framework that combines the Fast Segment Anything model with a semantic labeling pipeline to achieve real-time performance without sacrificing accuracy. FastSAM…
Real-Time Semantic SegmentationCataractSAM-2: A Domain-Adapted Model for Anterior Segment Surgery Segmentation and Scalable Ground-Truth Annotation
We present CataractSAM-2, a domain-adapted extension of Meta's Segment Anything Model 2, designed for real-time semantic segmentation of cataract ophthalmic surgery videos with high accuracy. Positioned at the intersecti…
Real-Time Semantic SegmentationZero-shot GeneralizationReal-Time Semantic Segmentation on FPGA for Autonomous Vehicles Using LMIINet with the CGRA4ML Framework
Semantic segmentation has emerged as a fundamental problem in computer vision, gaining particular importance in real-time applications such as autonomous driving. The main challenge is achieving high accuracy while opera…
Real-Time Semantic SegmentationAutonomous VehiclesAutonomous Driving