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 26–50 of 1723 papers

TitleStatusHype
Generalized Robot 3D Vision-Language Model with Fast Rendering and Pre-Training Vision-Language AlignmentCode3
Monkey: Image Resolution and Text Label Are Important Things for Large Multi-modal ModelsCode3
iDisc: Internal Discretization for Monocular Depth EstimationCode3
SurroundOcc: Multi-Camera 3D Occupancy Prediction for Autonomous DrivingCode3
Feed-Forward SceneDINO for Unsupervised Semantic Scene CompletionCode2
SIU3R: Simultaneous Scene Understanding and 3D Reconstruction Beyond Feature AlignmentCode2
Tackling View-Dependent Semantics in 3D Language Gaussian SplattingCode2
Scene-Centric Unsupervised Panoptic SegmentationCode2
Towards Generating Realistic 3D Semantic Training Data for Autonomous DrivingCode2
COB-GS: Clear Object Boundaries in 3DGS Segmentation Based on Boundary-Adaptive Gaussian SplittingCode2
SuperFlow++: Enhanced Spatiotemporal Consistency for Cross-Modal Data PretrainingCode2
PolarFree: Polarization-based Reflection-free ImagingCode2
IRef-VLA: A Benchmark for Interactive Referential Grounding with Imperfect Language in 3D ScenesCode2
Crab: A Unified Audio-Visual Scene Understanding Model with Explicit CooperationCode2
TrackOcc: Camera-based 4D Panoptic Occupancy TrackingCode2
Chameleon: Fast-slow Neuro-symbolic Lane Topology ExtractionCode2
An Egocentric Vision-Language Model based Portable Real-time Smart AssistantCode2
Inst3D-LMM: Instance-Aware 3D Scene Understanding with Multi-modal Instruction TuningCode2
NavRAG: Generating User Demand Instructions for Embodied Navigation through Retrieval-Augmented LLMCode2
VideoLifter: Lifting Videos to 3D with Fast Hierarchical Stereo AlignmentCode2
3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene UnderstandingCode2
AutoTrust: Benchmarking Trustworthiness in Large Vision Language Models for Autonomous DrivingCode2
RelationField: Relate Anything in Radiance FieldsCode2
DINO-Foresight: Looking into the Future with DINOCode2
Emma-X: An Embodied Multimodal Action Model with Grounded Chain of Thought and Look-ahead Spatial ReasoningCode2
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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