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 581–590 of 1723 papers

TitleStatusHype
Overlap-Aware Feature Learning for Robust Unsupervised Domain Adaptation for 3D Semantic Segmentation—0
Ross3D: Reconstructive Visual Instruction Tuning with 3D-Awareness—0
TransforMerger: Transformer-based Voice-Gesture Fusion for Robust Human-Robot Communication—0
CoMatcher: Multi-View Collaborative Feature Matching—0
Zero-Shot 4D Lidar Panoptic Segmentation—0
Context-Aware Human Behavior Prediction Using Multimodal Large Language Models: Challenges and Insights—0
PhysPose: Refining 6D Object Poses with Physical Constraints—0
Evaluating Compositional Scene Understanding in Multimodal Generative ModelsCode0
Open-Vocabulary Semantic Segmentation with Uncertainty Alignment for Robotic Scene Understanding in Indoor Building Environments—0
Empowering Large Language Models with 3D Situation Awareness—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