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 1471–1480 of 1723 papers

TitleStatusHype
Auto-Embedding Generative Adversarial Networks for High Resolution Image SynthesisCode0
Veritatem Dies Aperit- Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding ApproachCode0
Scene Understanding for Autonomous Manipulation with Deep Learning—0
Monocular 3D Object Detection with Pseudo-LiDAR Point CloudCode0
Quantitative Depth Quality Assessment of RGBD Cameras At Close Range Using 3D Printed FixturesCode0
Affordance Learning In Direct Perception for Autonomous Driving—0
Real time backbone for semantic segmentation—0
Instance- and Category-level 6D Object Pose Estimation—0
Building an Affordances Map with Interactive Perception—0
Hierarchy Denoising Recursive Autoencoders for 3D Scene Layout Prediction—0
Show:102550
← PrevPage 148 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