Papers Real-Time Semantic Segmentation
“Real-Time Semantic Segmentation” 태그가 달린 논문 155편 · 필터 해제
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 DrivingSelf-Supervised Learning to Fly using Efficient Semantic Segmentation and Metric Depth Estimation for Low-Cost Autonomous UAVs
This paper presents a vision-only autonomous flight system for small UAVs operating in controlled indoor environments. The system combines semantic segmentation with monocular depth estimation to enable obstacle avoidanc…
Real-Time Semantic SegmentationMonocular Depth EstimationSelf-Supervised LearningComputational EfficiencyMulti-modal video data-pipelines for machine learning with minimal human supervision
The real-world is inherently multi-modal at its core. Our tools observe and take snapshots of it, in digital form, such as videos or sounds, however much of it is lost. Similarly for actions and information passing betwe…
Real-Time Semantic SegmentationDepth EstimationVision-Based Perception for Autonomous Vehicles in Off-Road Environment Using Deep Learning
Low-latency intelligent systems are required for autonomous driving on non-uniform terrain in open-pit mines and developing countries. This work proposes a perception system for autonomous vehicles on unpaved roads and o…
Real-Time Semantic SegmentationAutonomous VehiclesAutonomous DrivingBEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation
Real-time semantic segmentation presents the dual challenge of designing efficient architectures that capture large receptive fields for semantic understanding while also refining detailed contours. Vision transformers m…
Real-Time Semantic SegmentationReal Time Semantic Segmentation of High Resolution Automotive LiDAR Scans
In recent studies, numerous previous works emphasize the importance of semantic segmentation of LiDAR data as a critical component to the development of driver-assistance systems and autonomous vehicles. However, many st…
Autonomous VehiclesReal-Time Semantic SegmentationSegmentationSemantic SegmentationReal-Time Semantic Segmentation of Aerial Images Using an Embedded U-Net: A Comparison of CPU, GPU, and FPGA Workflows
This study introduces a lightweight U-Net model optimized for real-time semantic segmentation of aerial images, targeting the efficient utilization of Commercial Off-The-Shelf (COTS) embedded computing platforms. We main…
CPUGPUReal-Time Semantic SegmentationSemantic SegmentationGolden Cudgel Network for Real-Time Semantic Segmentation
Recent real-time semantic segmentation models, whether single-branch or multi-branch, achieve good performance and speed. However, their speed is limited by multi-path blocks, and some depend on high-performance teacher …
Real-Time Semantic SegmentationSemantic SegmentationContextFormer: Redefining Efficiency in Semantic Segmentation
Semantic segmentation assigns labels to pixels in images, a critical yet challenging task in computer vision. Convolutional methods, although capturing local dependencies well, struggle with long-range relationships. Vis…
Real-Time Semantic SegmentationSemantic SegmentationEfficient Semantic Segmentation via Lightweight Multiple-Information Interaction Network
Recently, integrating the local modeling capabilities of Convolutional Neural Networks (CNNs) with the global dependency strengths of Transformers has created a sensation in the semantic segmentation community. However, …
GPUReal-Time Semantic SegmentationSemantic SegmentationICFRNet: Image Complexity Prior Guided Feature Refinement for Real-time Semantic Segmentation
In this paper, we leverage image complexity as a prior for refining segmentation features to achieve accurate real-time semantic segmentation. The design philosophy is based on the observation that different pixel region…
PhilosophyReal-Time Semantic SegmentationSegmentationSemantic SegmentationCSFNet: A Cosine Similarity Fusion Network for Real-Time RGB-X Semantic Segmentation of Driving Scenes
Semantic segmentation, as a crucial component of complex visual interpretation, plays a fundamental role in autonomous vehicle vision systems. Recent studies have significantly improved the accuracy of semantic segmentat…
Autonomous VehiclesImage SegmentationReal-Time Semantic SegmentationRGBD Semantic Segmentation+4Reparameterizable Dual-Resolution Network for Real-time Semantic Segmentation
Semantic segmentation plays a key role in applications such as autonomous driving and medical image. Although existing real-time semantic segmentation models achieve a commendable balance between accuracy and speed, thei…
Autonomous DrivingReal-Time Semantic SegmentationSegmentationSemantic SegmentationPyramidMamba: Rethinking Pyramid Feature Fusion with Selective Space State Model for Semantic Segmentation of Remote Sensing Imagery
Semantic segmentation, as a basic tool for intelligent interpretation of remote sensing images, plays a vital role in many Earth Observation (EO) applications. Nowadays, accurate semantic segmentation of remote sensing i…
DecoderEarth ObservationMambaReal-Time Semantic Segmentation+3DSNet: A Novel Way to Use Atrous Convolutions in Semantic Segmentation
Atrous convolutions are employed as a method to increase the receptive field in semantic segmentation tasks. However, in previous works of semantic segmentation, it was rarely employed in the shallow layers of the model.…
Real-Time Semantic SegmentationSemantic Segmentation