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 101–125 of 1723 papers

TitleStatusHype
AutoTrust: Benchmarking Trustworthiness in Large Vision Language Models for Autonomous DrivingCode2
Safety-Enhanced Autonomous Driving Using Interpretable Sensor Fusion TransformerCode2
GroupViT: Semantic Segmentation Emerges from Text SupervisionCode2
GALIP: Generative Adversarial CLIPs for Text-to-Image SynthesisCode2
Delving into Multi-modal Multi-task Foundation Models for Road Scene Understanding: From Learning Paradigm PerspectivesCode2
A Unified Framework for 3D Scene UnderstandingCode2
Feed-Forward SceneDINO for Unsupervised Semantic Scene CompletionCode2
FusionVision: A comprehensive approach of 3D object reconstruction and segmentation from RGB-D cameras using YOLO and fast segment anythingCode2
Diffusion-based Generation, Optimization, and Planning in 3D ScenesCode2
StableSemantics: A Synthetic Language-Vision Dataset of Semantic Representations in Naturalistic ImagesCode2
Gaussian Grouping: Segment and Edit Anything in 3D ScenesCode2
HAKE: A Knowledge Engine Foundation for Human Activity UnderstandingCode2
Tackling View-Dependent Semantics in 3D Language Gaussian SplattingCode2
TaskExpert: Dynamically Assembling Multi-Task Representations with Memorial Mixture-of-ExpertsCode2
EmbodiedScan: A Holistic Multi-Modal 3D Perception Suite Towards Embodied AICode2
DINO-Foresight: Looking into the Future with DINOCode2
Event-aided Semantic Scene CompletionCode1
Estimating Generic 3D Room Structures from 2D AnnotationsCode1
Event-based Motion Segmentation with Spatio-Temporal Graph CutsCode1
3DMIT: 3D Multi-modal Instruction Tuning for Scene UnderstandingCode1
A Review of Panoptic Segmentation for Mobile Mapping Point CloudsCode1
EndoChat: Grounded Multimodal Large Language Model for Endoscopic SurgeryCode1
A Survey on Deep Learning Technique for Video SegmentationCode1
Estimating and Exploiting the Aleatoric Uncertainty in Surface Normal EstimationCode1
Advances in Deep Concealed 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