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 1476–1500 of 1723 papers

TitleStatusHype
Neural RGB->D Sensing: Depth and Uncertainty from a Video CameraCode0
Curriculum Model Adaptation with Synthetic and Real Data for Semantic Foggy Scene UnderstandingCode1
Learning Spatial Common Sense with Geometry-Aware Recurrent Networks—0
Impact of Ground Truth Annotation Quality on Performance of Semantic Image Segmentation of Traffic ConditionsCode0
Reasoning About Physical Interactions with Object-Oriented Prediction and Planning—0
Learning Direct Optimization for Scene Understanding—0
Not Using the Car to See the Sidewalk: Quantifying and Controlling the Effects of Context in Classification and Segmentation—0
An Intelligent Safety System for Human-Centered Semi-Autonomous Vehicles—0
Counterfactual Critic Multi-Agent Training for Scene Graph Generation—0
The Right (Angled) Perspective: Improving the Understanding of Road Scenes Using Boosted Inverse Perspective Mapping—0
Submodular Field Grammars: Representation, Inference, and Application to Image Parsing—0
Learning to Exploit Stability for 3D Scene Parsing—0
Multiview Based 3D Scene Understanding On Partial Point Sets—0
ShelfNet for Fast Semantic SegmentationCode0
MonoGRNet: A Geometric Reasoning Network for Monocular 3D Object LocalizationCode0
IDD: A Dataset for Exploring Problems of Autonomous Navigation in Unconstrained EnvironmentsCode0
A pooling based scene text proposal technique for scene text reading in the wild—0
Artificial Color Constancy via GoogLeNet with Angular Loss FunctionCode0
Sensor Adaptation for Improved Semantic Segmentation of Overhead Imagery—0
Toward Driving Scene Understanding: A Dataset for Learning Driver Behavior and Causal Reasoning—0
Cooperative Holistic Scene Understanding: Unifying 3D Object, Layout, and Camera Pose EstimationCode0
UAVid: A Semantic Segmentation Dataset for UAV ImageryCode0
Multi-Task Learning as Multi-Objective OptimizationCode2
Diagnostics in Semantic Segmentation—0
Semantic and structural image segmentation for prosthetic vision—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