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 1226–1250 of 1723 papers

TitleStatusHype
Spatiotemporal Event Graphs for Dynamic Scene Understanding—0
Spatiotemporal Learning of Dynamic Gestures from 3D Point Cloud Data—0
SpectralGaussians: Semantic, spectral 3D Gaussian splatting for multi-spectral scene representation, visualization and analysis—0
SpeedMachines: Anytime Structured Prediction—0
Spherical World-Locking for Audio-Visual Localization in Egocentric Videos—0
SplatTalk: 3D VQA with Gaussian Splatting—0
SpSequenceNet: Semantic Segmentation Network on 4D Point Clouds—0
sshELF: Single-Shot Hierarchical Extrapolation of Latent Features for 3D Reconstruction from Sparse-Views—0
SSNet: Saliency Prior and State Space Model-based Network for Salient Object Detection in RGB-D Images—0
StandardSim: A Synthetic Dataset For Retail Environments—0
Stochastic Future Prediction in Real World Driving Scenarios—0
Str-L Pose: Integrating Point and Structured Line for Relative Pose Estimation in Dual-Graph—0
Semantic and structural image segmentation for prosthetic vision—0
Structural Concept Learning via Graph Attention for Multi-Level Rearrangement Planning—0
Structured agents for physical construction—0
Structured Generative Models for Scene Understanding—0
Neural Language of Thought Models—0
Style-transfer based Speech and Audio-visual Scene Understanding for Robot Action Sequence Acquisition from Videos—0
Submodular Field Grammars: Representation, Inference, and Application to Image Parsing—0
SUN RGB-D: A RGB-D Scene Understanding Benchmark Suite—0
SUPER: A Novel Lane Detection System—0
SuperGSeg: Open-Vocabulary 3D Segmentation with Structured Super-Gaussians—0
Surgical Scene Understanding in the Era of Foundation AI Models: A Comprehensive Review—0
SurgiSAM2: Fine-tuning a foundational model for surgical video anatomy segmentation and detection—0
SurGNN: Explainable visual scene understanding and assessment of surgical skill using graph neural networks—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