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 1121–1130 of 1723 papers

TitleStatusHype
Patch2CAD: Patchwise Embedding Learning for In-the-Wild Shape Retrieval from a Single Image—0
Panoramic Depth Estimation via Supervised and Unsupervised Learning in Indoor ScenesCode0
Deployment of Deep Neural Networks for Object Detection on Edge AI Devices with Runtime Optimization—0
Instance Segmentation in 3D Scenes using Semantic Superpoint Tree NetworksCode1
A Hybrid Sparse-Dense Monocular SLAM System for Autonomous DrivingCode1
Indoor Semantic Scene Understanding using Multi-modality Fusion—0
UniNet: A Unified Scene Understanding Network and Exploring Multi-Task Relationships through the Lens of Adversarial AttacksCode0
Learning Multi-Granular Spatio-Temporal Graph Network for Skeleton-based Action RecognitionCode1
Self-supervised Learning of Occlusion Aware Flow Guided 3D Geometry Perception with Adaptive Cross Weighted Loss from Monocular Videos—0
One-Shot Object Affordance Detection in the WildCode1
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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