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 301–325 of 1723 papers

TitleStatusHype
Uncertainty-aware Panoptic SegmentationCode1
MGNet: Monocular Geometric Scene Understanding for Autonomous DrivingCode1
IBISCape: A Simulated Benchmark for multi-modal SLAM Systems Evaluation in Large-scale Dynamic EnvironmentsCode1
Panoramic Panoptic Segmentation: Insights Into Surrounding Parsing for Mobile Agents via Unsupervised Contrastive LearningCode1
Expressive Scene Graph Generation Using Commonsense Knowledge Infusion for Visual Understanding and ReasoningCode1
Spatiality-guided Transformer for 3D Dense Captioning on Point CloudsCode1
P3Depth: Monocular Depth Estimation with a Piecewise Planarity PriorCode1
Online panoptic 3D reconstruction as a Linear Assignment ProblemCode1
Point Scene Understanding via Disentangled Instance Mesh ReconstructionCode1
Collaborative Transformers for Grounded Situation RecognitionCode1
Learning to Answer Questions in Dynamic Audio-Visual ScenariosCode1
MuKEA: Multimodal Knowledge Extraction and Accumulation for Knowledge-based Visual Question AnsweringCode1
WeakM3D: Towards Weakly Supervised Monocular 3D Object DetectionCode1
Deep learning for radar data exploitation of autonomous vehicleCode1
Bending Reality: Distortion-aware Transformers for Adapting to Panoramic Semantic SegmentationCode1
TransKD: Transformer Knowledge Distillation for Efficient Semantic SegmentationCode1
RIConv++: Effective Rotation Invariant Convolutions for 3D Point Clouds Deep LearningCode1
RescueNet: A High Resolution UAV Semantic Segmentation Benchmark Dataset for Natural Disaster Damage AssessmentCode1
ReorientBot: Learning Object Reorientation for Specific-Posed PlacementCode1
3DRM:Pair-wise relation module for 3D object detectionCode1
SafePicking: Learning Safe Object Extraction via Object-Level MappingCode1
Transformers in Self-Supervised Monocular Depth Estimation with Unknown Camera IntrinsicsCode1
Global-Reasoned Multi-Task Learning Model for Surgical Scene UnderstandingCode1
MonoDistill: Learning Spatial Features for Monocular 3D Object DetectionCode1
Point Cloud Pre-Training With Natural 3D StructuresCode1
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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