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 1276–1300 of 1723 papers

TitleStatusHype
TGP: Two-modal occupancy prediction with 3D Gaussian and sparse points for 3D Environment Awareness—0
The Devil is in the Boundary: Exploiting Boundary Representation for Basis-based Instance Segmentation—0
The H3D Dataset for Full-Surround 3D Multi-Object Detection and Tracking in Crowded Urban Scenes—0
The Mapillary Vistas Dataset for Semantic Understanding of Street Scenes—0
The Right (Angled) Perspective: Improving the Understanding of Road Scenes Using Boosted Inverse Perspective Mapping—0
These Magic Moments: Differentiable Uncertainty Quantification of Radiance Field Models—0
-MRF: Capturing Spatial and Semantic Structure in the Parameters for Scene Understanding—0
The toulouse vanishing points dataset—0
TinyRS-R1: Compact Multimodal Language Model for Remote Sensing—0
To complete or to estimate, that is the question: A Multi-Task Approach to Depth Completion and Monocular Depth Estimation—0
TopoMask: Instance-Mask-Based Formulation for the Road Topology Problem via Transformer-Based Architecture—0
TORNADO-Net: mulTiview tOtal vaRiatioN semAntic segmentation with Diamond inceptiOn module—0
Toward Driving Scene Understanding: A Dataset for Learning Driver Behavior and Causal Reasoning—0
Toward Explainable and Fine-Grained 3D Grounding through Referring Textual Phrases—0
Towards 3D Scene Understanding by Referring Synthetic Models—0
Towards Adapting ImageNet to Reality: Scalable Domain Adaptation with Implicit Low-rank Transformations—0
Towards A Unified Agent with Foundation Models—0
Towards Deeper and Better Multi-view Feature Fusion for 3D Semantic Segmentation—0
Towards Escaping from Language Bias and OCR Error: Semantics-Centered Text Visual Question Answering—0
Towards General Purpose Geometry-Preserving Single-View Depth Estimation—0
Towards Holistic Scene Understanding: Feedback Enabled Cascaded Classification Models—0
Towards holistic scene understanding: Semantic segmentation and beyond—0
Towards Localizing Structural Elements: Merging Geometrical Detection with Semantic Verification in RGB-D Data—0
Towards Multimodal Multitask Scene Understanding Models for Indoor Mobile Agents—0
Towards Robust Algorithms for Surgical Phase Recognition via Digital Twin-based Scene Representation—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