All-day Semantic Segmentation
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Benchmarks
All-day CityScapes
Most implemented
Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net
Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes
Papers
Interactive Learning of Intrinsic and Extrinsic Properties for All-day Semantic Segmentation
Scene appearance changes drastically throughout the day. Existing semantic segmentation methods mainly focus on well-lit daytime scenarios and are not well designed to cope with such great appearance changes. Naively usi…
AllAll-day Semantic SegmentationDomain AdaptationSemantic SegmentationRobustNet: Improving Domain Generalization in Urban-Scene Segmentation via Instance Selective Whitening
Enhancing the generalization capability of deep neural networks to unseen domains is crucial for safety-critical applications in the real world such as autonomous driving. To address this issue, this paper proposes a nov…
All-day Semantic SegmentationAutonomous DrivingDomain GeneralizationRobust Object Detection+1Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes
Semantic segmentation is a key technology for autonomous vehicles to understand the surrounding scenes. The appealing performances of contemporary models usually come at the expense of heavy computations and lengthy infe…
All-day Semantic SegmentationAutonomous VehiclesGPUReal-Time Semantic Segmentation+2Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net
Convolutional neural networks (CNNs) have achieved great successes in many computer vision problems. Unlike existing works that designed CNN architectures to improve performance on a single task of a single domain and no…
All-day Semantic SegmentationDomain AdaptationDomain GeneralizationRobust Object Detection+1