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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 731–740 of 1723 papers

TitleStatusHype
Open-Vocabulary Octree-Graph for 3D Scene Understanding—0
RoboSpatial: Teaching Spatial Understanding to 2D and 3D Vision-Language Models for Robotics—0
UniGaussian: Driving Scene Reconstruction from Multiple Camera Models via Unified Gaussian Representations—0
Multimodal 3D Reasoning Segmentation with Complex Scenes—0
Classification of Geographical Land Structure Using Convolution Neural Network and Transfer Learning—0
Calibrated and Efficient Sampling-Free Confidence Estimation for LiDAR Scene Semantic Segmentation—0
MGNiceNet: Unified Monocular Geometric Scene UnderstandingCode0
The ADUULM-360 Dataset -- A Multi-Modal Dataset for Depth Estimation in Adverse WeatherCode0
Reducing Label Dependency for Underwater Scene Understanding: A Survey of Datasets, Techniques and Applications—0
Memory-Augmented Multimodal LLMs for Surgical VQA via Self-Contained Inquiry—0
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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