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 276–300 of 1723 papers

TitleStatusHype
GFF: Gated Fully Fusion for Semantic SegmentationCode1
Generating Visual Spatial Description via Holistic 3D Scene UnderstandingCode1
Global Aggregation then Local Distribution in Fully Convolutional NetworksCode1
General Geometry-aware Weakly Supervised 3D Object DetectionCode1
Context Prior for Scene SegmentationCode1
3D Neural Embedding Likelihood: Probabilistic Inverse Graphics for Robust 6D Pose EstimationCode1
Global-Reasoned Multi-Task Learning Model for Surgical Scene UnderstandingCode1
Complementary Random Masking for RGB-Thermal Semantic SegmentationCode1
From General to Specific: Informative Scene Graph Generation via Balance AdjustmentCode1
F-ViTA: Foundation Model Guided Visible to Thermal TranslationCode1
Collaborative Transformers for Grounded Situation RecognitionCode1
FocusFlow: Boosting Key-Points Optical Flow Estimation for Autonomous DrivingCode1
Few-Shot Object Detection and Viewpoint Estimation for Objects in the WildCode1
FloodNet: A High Resolution Aerial Imagery Dataset for Post Flood Scene UnderstandingCode1
FPS-Net: A Convolutional Fusion Network for Large-Scale LiDAR Point Cloud SegmentationCode1
Affordance Transfer Learning for Human-Object Interaction DetectionCode1
FreDSNet: Joint Monocular Depth and Semantic Segmentation with Fast Fourier ConvolutionsCode1
GOV-NeSF: Generalizable Open-Vocabulary Neural Semantic FieldsCode1
From Multi-View to Hollow-3D: Hallucinated Hollow-3D R-CNN for 3D Object DetectionCode1
HiLo: Exploiting High Low Frequency Relations for Unbiased Panoptic Scene Graph GenerationCode1
Exploiting Edge-Oriented Reasoning for 3D Point-based Scene Graph AnalysisCode1
A Survey on Deep Learning Technique for Video SegmentationCode1
Exploring Data-Efficient 3D Scene Understanding with Contrastive Scene ContextsCode1
4D Panoptic LiDAR SegmentationCode1
Explainable Object-induced Action Decision for Autonomous VehiclesCode1
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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