SOTAVerified

Scene Understanding

Scene understanding involves interpreting the visual information of a scene, including objects, their spatial relationships, and the overall layout. It goes beyond simple object recognition by considering the context and how objects relate to each other and the environment.

Papers

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Showing 226–250 of 1723 papers

TitleStatusHype
MLRSNet: A Multi-label High Spatial Resolution Remote Sensing Dataset for Semantic Scene UnderstandingCode1
CAKES: Channel-wise Automatic KErnel Shrinking for Efficient 3D NetworksCode1
Knowledge Distillation from 3D to Bird's-Eye-View for LiDAR Semantic SegmentationCode1
AVSegFormer: Audio-Visual Segmentation with TransformerCode1
CamContextI2V: Context-aware Controllable Video GenerationCode1
DeepScores -- A Dataset for Segmentation, Detection and Classification of Tiny ObjectsCode1
F-ViTA: Foundation Model Guided Visible to Thermal TranslationCode1
FocusFlow: Boosting Key-Points Optical Flow Estimation for Autonomous DrivingCode1
Campus3D: A Photogrammetry Point Cloud Benchmark for Hierarchical Understanding of Outdoor SceneCode1
Joint 2D-3D-Semantic Data for Indoor Scene UnderstandingCode1
From General to Specific: Informative Scene Graph Generation via Balance AdjustmentCode1
From Multi-View to Hollow-3D: Hallucinated Hollow-3D R-CNN for 3D Object DetectionCode1
MSeg: A Composite Dataset for Multi-domain Semantic SegmentationCode1
Lane Graph Estimation for Scene Understanding in Urban DrivingCode1
Deep Learning for Event-based Vision: A Comprehensive Survey and BenchmarksCode1
Instance-wise Occlusion and Depth Orders in Natural ScenesCode1
MuKEA: Multimodal Knowledge Extraction and Accumulation for Knowledge-based Visual Question AnsweringCode1
A Review of Panoptic Segmentation for Mobile Mapping Point CloudsCode1
Deep learning for radar data exploitation of autonomous vehicleCode1
IRS: A Large Naturalistic Indoor Robotics Stereo Dataset to Train Deep Models for Disparity and Surface Normal EstimationCode1
General Geometry-aware Weakly Supervised 3D Object DetectionCode1
Language-Assisted 3D Feature Learning for Semantic Scene UnderstandingCode1
All-Day Multi-Camera Multi-Target TrackingCode1
DD-PPO: Learning Near-Perfect PointGoal Navigators from 2.5 Billion FramesCode1
Auto-Panoptic: Cooperative Multi-Component Architecture Search for Panoptic SegmentationCode1
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All datasetsSemantic Scene Understanding Challenge (passive actuation & ground-truth localisation)ADE20K valSemantic Scene Understanding Challenge (active actuation & ground-truth localisation)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ACRV BaselineOMQ0.44—Unverified
2Team VGAI (TCS Research)OMQ0.37—Unverified
3Demo_semantic_SLAMOMQ0.11—Unverified
#ModelMetricClaimedVerifiedStatus
1CPN(ResNet-101)Mean IoU46.3—Unverified
#ModelMetricClaimedVerifiedStatus
1ACRV BaselineOMQ0.35—Unverified