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 1401–1425 of 1723 papers

TitleStatusHype
Addressing the Sim2Real Gap in Robotic 3D Object Classification—0
Leveraging Auxiliary Text for Deep Recognition of Unseen Visual Relationships—0
GANspection—0
Deep Contextual Attention for Human-Object Interaction Detection—0
Deep Semantic Segmentation of Natural and Medical Images: A Review—0
Semantic Understanding of Foggy Scenes with Purely Synthetic DataCode0
Using Image Priors to Improve Scene Understanding—0
Real-Time Semantic Stereo Matching—0
Depth-Induced Multi-Scale Recurrent Attention Network for Saliency DetectionCode0
Multi-view PointNet for 3D Scene Understanding—0
Dynamic Interaction-Aware Scene Understanding for Reinforcement Learning in Autonomous Driving—0
Meta Learning with Differentiable Closed-form Solver for Fast Video Object Segmentation—0
On the Pareto Efficiency of Quantized CNN—0
Large Scale Joint Semantic Re-Localisation and Scene Understanding via Globally Unique Instance Coordinate Regression—0
Simultaneous Segmentation and Recognition: Towards more accurate Ego Gesture Recognition—0
Pose-aware Multi-level Feature Network for Human Object Interaction DetectionCode0
Multi-Task Learning for Automotive Foggy Scene Understanding via Domain Adaptation to an Illumination-Invariant Representation—0
Visuomotor Understanding for Representation Learning of Driving Scenes—0
Semantic Foreground Inpainting from Weak SupervisionCode0
DublinCity: Annotated LiDAR Point Cloud and its Applications—0
Holistic++ Scene Understanding: Single-view 3D Holistic Scene Parsing and Human Pose Estimation with Human-Object Interaction and Physical Commonsense—0
Texture Underfitting for Domain Adaptation—0
Rotation Invariant Convolutions for 3D Point Clouds Deep LearningCode0
RIO: 3D Object Instance Re-Localization in Changing Indoor EnvironmentsCode0
To complete or to estimate, that is the question: A Multi-Task Approach to Depth Completion and Monocular Depth Estimation—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