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 1241–1250 of 1723 papers

TitleStatusHype
Navigation-Oriented Scene Understanding for Robotic Autonomy: Learning to Segment Driveability in Egocentric Images—0
On the Sins of Image Synthesis Loss for Self-supervised Depth Estimation—0
Residual 3D Scene Flow Learning with Context-Aware Feature Extraction—0
Single Image 3D Object Estimation with Primitive Graph NetworksCode0
RefineCap: Concept-Aware Refinement for Image Captioning—0
Improving Building Segmentation for Off-Nadir Satellite Imagery—0
Binaural SoundNet: Predicting Semantics, Depth and Motion with Binaural Sounds—0
Multi-task learning from fixed-wing UAV images for 2D/3D city modeling—0
Deep Bayesian Image Set Classification: A Defence Approach against Adversarial Attacks—0
A Multiple-View Geometric Model for Specularity Prediction on General Curved Surfaces—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