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 1176–1200 of 1723 papers

TitleStatusHype
BBBD: Bounding Box Based Detector for Occlusion Detection and Order Recovery—0
SceneTrilogy: On Human Scene-Sketch and its Complementarity with Photo and Text—0
Graph-DETR3D: Rethinking Overlapping Regions for Multi-View 3D Object Detection—0
Can Foundation Models Perform Zero-Shot Task Specification For Robot Manipulation?—0
SELMA: SEmantic Large-scale Multimodal Acquisitions in Variable Weather, Daytime and Viewpoints—0
Attention Mechanism based Cognition-level Scene Understanding—0
MTANet: Multitask-Aware Network With Hierarchical Multimodal Fusion for RGB-T Urban Scene Understanding—0
Multi-Task Learning for Visual Scene Understanding—0
Semi-supervised and Deep learning Frameworks for Video Classification and Key-frame Identification—0
Towards Escaping from Language Bias and OCR Error: Semantics-Centered Text Visual Question Answering—0
Self-Supervised Road Layout Parsing with Graph Auto-EncodingCode0
Towards 3D Scene Understanding by Referring Synthetic Models—0
Iwin: Human-Object Interaction Detection via Transformer with Irregular Windows—0
Neural Part Priors: Learning to Optimize Part-Based Object Completion in RGB-D Scans—0
Deep Point Cloud Simplification for High-quality Surface Reconstruction—0
RAUM-VO: Rotational Adjusted Unsupervised Monocular Visual Odometry—0
On Steering Multi-Annotations per Sample for Multi-Task Learning—0
Fast Neural Architecture Search for Lightweight Dense Prediction Networks—0
Hybrid Optimized Deep Convolution Neural Network based Learning Model for Object Detection—0
Movies2Scenes: Using Movie Metadata to Learn Scene Representation—0
CARL-D: A vision benchmark suite and large scale dataset for vehicle detection and scene segmentationCode0
From Node to Graph: Joint Reasoning on Visual-Semantic Relational Graph for Zero-Shot DetectionCode0
Catch Me if You Can: A Novel Task for Detection of Covert Geo-Locations (CGL)—0
StandardSim: A Synthetic Dataset For Retail Environments—0
Image-based Navigation in Real-World Environments via Multiple Mid-level Representations: Fusion Models, Benchmark and Efficient EvaluationCode0
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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