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 1291–1300 of 1723 papers

TitleStatusHype
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
Show:102550
← PrevPage 130 of 173Next →
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