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 726–750 of 1723 papers

TitleStatusHype
Deep Reinforcement Learning on a Budget: 3D Control and Reasoning Without a SupercomputerCode0
Benchmarking Feature Upsampling Methods for Vision Foundation Models using Interactive SegmentationCode0
Interpretable Visual Understanding with Cognitive Attention NetworkCode0
P2AT: Pyramid Pooling Axial Transformer for Real-time Semantic SegmentationCode0
Single Image 3D Object Estimation with Primitive Graph NetworksCode0
Exploiting Temporal Coherence for Multi-modal Video Categorization—0
Exploiting High Level Scene Cues in Stereo Reconstruction—0
Explicit3D: Graph Network with Spatial Inference for Single Image 3D Object Detection—0
Challenges for Monocular 6D Object Pose Estimation in Robotics—0
ArK: Augmented Reality with Knowledge Interactive Emergent Ability—0
Explainable Scene Understanding with Qualitative Representations and Graph Neural Networks—0
Expanding Frozen Vision-Language Models without Retraining: Towards Improved Robot Perception—0
Exosense: A Vision-Based Scene Understanding System For Exoskeletons—0
Argus: Leveraging Multiview Images for Improved 3-D Scene Understanding With Large Language Models—0
Adversarial Attacks on Monocular Depth Estimation—0
ExCap3D: Expressive 3D Scene Understanding via Object Captioning with Varying Detail—0
EvSegSNN: Neuromorphic Semantic Segmentation for Event Data—0
EvidMTL: Evidential Multi-Task Learning for Uncertainty-Aware Semantic Surface Mapping from Monocular RGB Images—0
Every SAM Drop Counts: Embracing Semantic Priors for Multi-Modality Image Fusion and Beyond—0
Event fields: Capturing light fields at high speed, resolution, and dynamic range—0
Category-Level and Open-Set Object Pose Estimation for Robotics—0
Evaluation of Multimodal Semantic Segmentation using RGB-D Data—0
Catch Me if You Can: A Novel Task for Detection of Covert Geo-Locations (CGL)—0
A Review on Visual-SLAM: Advancements from Geometric Modelling to Learning-based Semantic Scene Understanding—0
Advancing the Understanding of Fine-Grained 3D Forest Structures using Digital Cousins and Simulation-to-Reality: Methods and Datasets—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