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 426–450 of 1723 papers

TitleStatusHype
MonoDistill: Learning Spatial Features for Monocular 3D Object DetectionCode1
PanoOcc: Unified Occupancy Representation for Camera-based 3D Panoptic SegmentationCode1
MSeg: A Composite Dataset for Multi-domain Semantic SegmentationCode1
Explainable Object-induced Action Decision for Autonomous VehiclesCode1
TextSLAM: Visual SLAM with Planar Text FeaturesCode1
OK-VQA: A Visual Question Answering Benchmark Requiring External KnowledgeCode1
MuKEA: Multimodal Knowledge Extraction and Accumulation for Knowledge-based Visual Question AnsweringCode1
Multi3DRefer: Grounding Text Description to Multiple 3D ObjectsCode1
DTCLMapper: Dual Temporal Consistent Learning for Vectorized HD Map ConstructionCode1
Panoptic 3D Scene Reconstruction From a Single RGB ImageCode1
Dual-Hybrid Attention Network for Specular Highlight RemovalCode1
Multimodal Dataset for Localization, Mapping and Crop Monitoring in Citrus Tree FarmsCode1
Egocentric Scene Understanding via Multimodal Spatial RectifierCode1
Cityscapes-Panoptic-Parts and PASCAL-Panoptic-Parts datasets for Scene UnderstandingCode1
Efficient Multi-Task RGB-D Scene Analysis for Indoor EnvironmentsCode1
Dynamic Graph Message Passing Networks for Visual RecognitionCode1
Bridging the Domain Gap: Self-Supervised 3D Scene Understanding with Foundation ModelsCode1
Exploiting Edge-Oriented Reasoning for 3D Point-based Scene Graph AnalysisCode1
Dynamic Scene Understanding through Object-Centric Voxelization and Neural RenderingCode1
Multi-Scale Attention for Audio Question AnsweringCode1
Multi-stage Factorized Spatio-Temporal Representation for RGB-D Action and Gesture RecognitionCode1
P2T: Pyramid Pooling Transformer for Scene UnderstandingCode1
ARKitScenes: A Diverse Real-World Dataset For 3D Indoor Scene Understanding Using Mobile RGB-D DataCode1
ECLAIR: A High-Fidelity Aerial LiDAR Dataset for Semantic SegmentationCode1
3UR-LLM: An End-to-End Multimodal Large Language Model for 3D Scene UnderstandingCode1
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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